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If you would like to experiment with a different UR robot: - #. Delete the UR10e from the scene. - #. Find the alternative robot in Isaac Sim's robot assets folder and drag it onto the table in the scene. + #. Find the alternative robot in Isaac Sim's robot assets folder and drag it onto the table in the scene. #. Edit the Action Graph so that the ``ROS2 Publish Joint State`` and ``Articulation Controller`` nodes refer to the new robot, and save the USD file. #. After the scene is fully loaded, click **Play**. diff --git a/public/_sources/concepts/stereo_depth/foundationstereo/tutorial_isaac_sim.rst.txt b/public/_sources/concepts/stereo_depth/foundationstereo/tutorial_isaac_sim.rst.txt index ce507e8b4..780c344db 100644 --- a/public/_sources/concepts/stereo_depth/foundationstereo/tutorial_isaac_sim.rst.txt +++ b/public/_sources/concepts/stereo_depth/foundationstereo/tutorial_isaac_sim.rst.txt @@ -50,14 +50,14 @@ Tutorial Walkthrough .. code:: bash ros2 launch isaac_ros_foundationstereo isaac_ros_foundationstereo_isaac_sim.launch.py \ - engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_576x960.engine + engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_576x960.engine .. tab:: Low Resolution (low_res) .. code:: bash ros2 launch isaac_ros_foundationstereo isaac_ros_foundationstereo_isaac_sim.launch.py \ - engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_320x736.engine \ + engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_320x736.engine \ model_input_width:=736 model_input_height:=320 The launch file will automatically open RViz configured to display: diff --git a/public/_sources/concepts/stereo_depth/foundationstereo/visualize_image.rst.txt b/public/_sources/concepts/stereo_depth/foundationstereo/visualize_image.rst.txt index 97418cac7..b969e6b92 100644 --- a/public/_sources/concepts/stereo_depth/foundationstereo/visualize_image.rst.txt +++ b/public/_sources/concepts/stereo_depth/foundationstereo/visualize_image.rst.txt @@ -23,14 +23,14 @@ To generate a disparity estimation from raw inputs: .. code:: bash ros2 launch isaac_ros_foundationstereo isaac_ros_foundationstereo.launch.py \ - engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_576x960.engine + engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_576x960.engine .. tab:: Low Resolution (low_res) .. code:: bash ros2 launch isaac_ros_foundationstereo isaac_ros_foundationstereo.launch.py \ - engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_320x736.engine \ + engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_320x736.engine \ model_input_width:=736 model_input_height:=320 3. Visualize and validate the output of the package: diff --git a/public/_sources/concepts/visual_global_localization/index.rst.txt b/public/_sources/concepts/visual_global_localization/index.rst.txt index 792c5157e..76adbd587 100644 --- a/public/_sources/concepts/visual_global_localization/index.rst.txt +++ b/public/_sources/concepts/visual_global_localization/index.rst.txt @@ -31,14 +31,13 @@ cuVGL uses external poses, such as those provided by a SLAM system, along with images to produce a keyframe database. This database is later used for global localization, making cuVGL a flexible component for systems that do not have global localization capabilities. +.. figure:: :ir_lfs:`` + :align: center + :width: 800px Map Creation Process ^^^^^^^^^^^^^^^^^^^^ -.. figure:: :ir_lfs:`` - :align: center - :width: 800px - The map creation process in cuVGL is unique as it consumes external poses and images to build a **keyframe database**, rather than generating a traditional map like a sparse feature map. @@ -56,16 +55,28 @@ The output map includes: Localization Process ^^^^^^^^^^^^^^^^^^^^ -.. figure:: :ir_lfs:`` +Localization in cuVGL is performed using stereo images for relative pose estimation. The process involves: + +* **image retrieval**: for the current input image, cuVGL retrieves the best matching candidates from the keyframe database using the BoW image retrieval index. +* **relative pose estimation**: after matching candidates are identified, the library computes the relative pose between the input stereo image and the map image candidate. +* **absolute pose calculation**: by applying the relative transform to the mapping pose of the map image (recorded during the mapping phase), cuVGL outputs an absolute pose for the current input image. + + +cuVSLAM Hinted Localization with cuVGL +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +.. figure:: :ir_lfs:`` :align: center :width: 800px -Localization in cuVGL is performed using stereo images for relative pose estimation. The process involves: +cuVGL provides an external initial global pose to bootstrap cuVSLAM localization. The workflow is as follows: -* **image retrieval**: for the current input image, cuVGL retrieves the best matching candidates from the keyframe database using the BoW image retrieval index. -* **relative pose estimation**: after matching candidates are identified, the library computes the relative pose between the input stereo image and the map image candidate. -* **absolute pose calculation**: by applying the relative transform to the mapping pose of the map image (recorded during the mapping phase), cuVGL outputs an absolute pose for the current input image. +- **map creation**: run cuVSLAM to estimate image poses and build a cuVSLAM map, then + use the poses and mapping images to generate a cuVGL map for localization. +- **localization**: launch cuVGL and cuVSLAM ROS nodes with their maps and stereo image inputs. + cuVGL first estimates a global pose to bootstrap cuVSLAM localization. Once cuVSLAM successfully + localizes, cuVGL stops and cuVSLAM starts to continuously localize in the map frame. .. note:: @@ -108,4 +119,5 @@ To get started with cuVGL, review the following examples: :maxdepth: 1 tutorials/tutorial_map_creation - tutorials/tutorial_localization + tutorials/tutorial_cuvgl_map_creation + tutorials/tutorial_cuvgl_localization diff --git a/public/_sources/concepts/visual_global_localization/tutorials/tutorial_localization.rst.txt b/public/_sources/concepts/visual_global_localization/tutorials/tutorial_cuvgl_localization.rst.txt similarity index 79% rename from public/_sources/concepts/visual_global_localization/tutorials/tutorial_localization.rst.txt rename to public/_sources/concepts/visual_global_localization/tutorials/tutorial_cuvgl_localization.rst.txt index 63b4d5932..a16647c01 100644 --- a/public/_sources/concepts/visual_global_localization/tutorials/tutorial_localization.rst.txt +++ b/public/_sources/concepts/visual_global_localization/tutorials/tutorial_cuvgl_localization.rst.txt @@ -1,7 +1,7 @@ Tutorial: Localization with cuVGL ================================= -After you have created a cuVGL map with :doc:`Tutorial: cuVGL Map Creation `, +After you have created a cuVGL map with :doc:`Tutorial: cuVGL Map Creation `, you can use it for localization. Use Global Localization Node in ROS 2 @@ -40,7 +40,7 @@ Live Localization in ROS 2 Use the following command to launch the localization node: -#. Create a map by following :doc:`Tutorial: cuVGL Map Creation `. +#. Create a map by following :doc:`Tutorial: cuVGL Map Creation `. #. Launch container and go to container's terminal. #. Inside container, export TensorRT engine files as described in :ref:`export_tensorrt_engine_files`. #. Inside container, run the following command to launch the localization node: @@ -64,8 +64,8 @@ We provide an end-to-end ROS launch file for replaying a rosbag and running glob runs global localization on incoming frames, even if a localization pose has already been computed. It also activates the 3D Lidar to create a point cloud overlay on the occupancy map using the result poses. -#. Create a map by following :doc:`Tutorial: cuVGL Map Creation `. -#. Record a localization rosbag using appropriate data recording tools. Please keep the localization trajectory within 1m from the map trajectory's coverage. +#. Create a map by following :doc:`Tutorial: cuVGL Map Creation `. +#. Record a localization rosbag using appropriate data recording tools. Keep the localization trajectory within 1m from the map trajectory's coverage. #. Inside container, export TensorRT engine files as described in :ref:`export_tensorrt_engine_files`. #. Inside container, install RViz: @@ -107,25 +107,25 @@ This section describes the coordinate frames that are involved in the :width: 300px :align: center -- ``base_frame``: The base frame of the robot or camera rig. It is assumed that - all cameras are rigidly mounted to this frame, such that the transforms between - the ``base_frame`` and the ``camera_optical_frames`` can assumed to be static. - The estimated odometry and SLAM pose will represent the pose of this frame. +#. ``base_frame``: The base frame of the robot or camera rig. It is assumed that + all cameras are rigidly mounted to this frame, such that the transforms between + the ``base_frame`` and the ``camera_optical_frames`` can assumed to be static. + The estimated odometry and SLAM pose will represent the pose of this frame. -- ``map_frame``: The frame corresponding to the origin of the map that cuVGL - creates or localizes in. The SLAM pose reported by cuVGL corresponds with - the transform ``map_frame`` -> ``base_frame``. +#. ``map_frame``: The frame corresponding to the origin of the map that cuVGL + creates or localizes in. The SLAM pose reported by cuVGL corresponds with + the transform ``map_frame`` -> ``base_frame``. -- ``camera_optical_frames``: The frames corresponding to the optical center of - every camera. The frame is expected to lie at the center of the camera lens - and oriented with the z-axis pointing in the view direction and the y-axis - pointing to the floor. +#. ``camera_optical_frames``: The frames corresponding to the optical center of + every camera. The frame is expected to lie at the center of the camera lens + and oriented with the z-axis pointing in the view direction and the y-axis + pointing to the floor. Troubleshooting ^^^^^^^^^^^^^^^ -- If localization frequently fails to return a pose, consider relaxing the rejection criteria, allowing it to return less confident results, by setting: ``vgl_localization_precision_level:=0``. -- To print more debug messages from the localization node, use launch parameters: ``vgl_verbose_logging:=True vgl_init_glog:=True vgl_glog_v:=1``. +#. If localization frequently fails to return a pose, consider relaxing the rejection criteria, allowing it to return less confident results, by setting: ``vgl_localization_precision_level:=0``. +#. To print more debug messages from the localization node, use launch parameters: ``vgl_verbose_logging:=True vgl_init_glog:=True vgl_glog_v:=1``. Use cuVGL in C++ diff --git a/public/_sources/concepts/visual_global_localization/tutorials/tutorial_cuvgl_map_creation.rst.txt b/public/_sources/concepts/visual_global_localization/tutorials/tutorial_cuvgl_map_creation.rst.txt new file mode 100644 index 000000000..c36f40517 --- /dev/null +++ b/public/_sources/concepts/visual_global_localization/tutorials/tutorial_cuvgl_map_creation.rst.txt @@ -0,0 +1,137 @@ +Tutorial: cuVGL Map Creation +=============================== + +End-to-End Visual and Occupancy Map Creation +-------------------------------------------- + +We provide an end-to-end script to create visual maps from ROS bags, +refer to :doc:`Tutorial: End-to-End Visual and Occupancy Map Creation `. +It outputs a cuVSLAM map, a cuVGL map, and an occupancy map in the same coordinate system. +The output maps can be used by cuVSLAM and cuVGL localization. + + +Create cuVGL Map Using cuSFM +---------------------------- + +You can switch to use cuSFM by setting the ``--use_cusfm`` option in the map creation script from the above tutorial, the command is: + +.. code-block:: bash + + ros2 run isaac_mapping_ros create_map_offline.py --sensor_data_bag= --base_output_folder= --use_cusfm + +It outputs a cuVGL map for cuVGL localization as in +:doc:`Tutorial: Localization with cuVGL ` +and an occupancy map. It doesn't output a cuVSLAM map, so it doesn't +support cuVSLAM localization. + +Create cuVGL Map Using Your Own SLAM Algorithm +---------------------------------------------- + +If you want to use your own SLAM algorithm to create the cuVGL map, you can follow these steps: + +#. Collect a rosbag using appropriate data recording tools. +#. Run your own SLAM algorithm to generate the poses. +#. Export TensorRT engine files as described in :ref:`Export TensorRT Engine Files `. +#. Extract images from the rosbags. You can use the following command to extract features from rosbags. + + Create a camera topic config that matches with your rosbag recording. + + .. code-block:: yaml + + stereo_cameras: + - name: my_camera + left: /my_camera/left/image_raw + left_camera_info: /my_camera/left/camera_info + right: /my_camera/right/image_raw + right_camera_info: /my_camera/right/camera_info + + .. code-block:: bash + + # Set following variables to your own paths + SENSOR_DATA_BAG="path_to_sensor_data.bag" + POSE_BAG="path_to_pose.bag" + MAP_FOLDER="path_to_map_folder" + POSE_TOPIC_NAME="topic_name_of_the_pose" + CAMERA_TOPIC_CONFIG="path_to_camera_topic_config.yaml" + + # Then extract the keyframes with image features from the rosbag + ros2 run isaac_mapping_ros rosbag_to_mapping_data \ + --sensor_data_bag_file=$SENSOR_DATA_BAG \ + --pose_bag_file=$POSE_BAG \ + --output_folder_path="$MAP_FOLDER/raw" \ + --min_inter_frame_rotation_degrees=5 \ + --min_inter_frame_distance=0.2 \ + --pose_topic_name=$POSE_TOPIC_NAME \ + --camera_topic_config=$CAMERA_TOPIC_CONFIG + + .. note:: + * Only ``geometry_msgs/msg/PoseStamped``, ``geometry_msgs/msg/PoseWithCovarianceStamped``, ``nav_msgs/msg/Odometry``, and ``nav_msgs/msg/Path`` message types are supported for pose type in the pose rosbag. Poses stored in the pose bag are in ``base_link`` frame. + * Change ``--min_inter_frame_rotation_degrees`` and ``--min_inter_frame_distance`` to your own values for proper density of the keyframes. Larger environments might require larger values. + + More documentation about the ``rosbag_to_mapping_data`` tool can be found in the :doc:`isaac_mapping_ros documentation `. + +#. Create cuVGL map with following command: + + .. code-block:: bash + + + # Create the global localization map, it will create bow index, bow vocabulary + ros2 run isaac_ros_visual_mapping create_cuvgl_map.py --map_folder=$MAP_FOLDER \ + --binary_folder_path $(ros2 pkg prefix isaac_ros_visual_mapping)/bin/visual_mapping \ + --config_folder_path $(ros2 pkg prefix --share isaac_ros_visual_mapping)/configs/isaac/ \ + --model_dir $(ros2 pkg prefix --share isaac_ros_visual_mapping)/models/ + + .. note:: + * If you export the TensorRT engine files, pass ``--model_dir $OUTPUT_MODEL_DIR`` when running ``create_cuvgl_map.py``. + * If you have a prebuilt vocabulary, pass ``--prebuilt_bow_vocabulary_folder `` when running ``create_cuvgl_map.py``. For example: + + .. code-block:: bash + + ros2 run isaac_ros_visual_mapping create_cuvgl_map.py --map_folder=$MAP_FOLDER --prebuilt_bow_vocabulary_folder= + + +Create cuVGL Map From Images +---------------------------- + +The map creation process in cuVGL requires two inputs: + +* Rectified Images (From stereo camera) +* Poses + +cuVGL extracts features from the images and saves them along with the corresponding poses. +The cuVGL map is structured as a folder that contains the following files: + +* ``keyframes``: This folder contains the features extracted from the raw images, with each individual keyframe saved as a binary protobuf file. +* ``keyframes/frames_meta.pb.txt``: This ``protobuf`` file contains metadata for the keyframes including timestamp, poses, and ``image_name``. +* ``bow_index.pb``: This is the bag-of-words index file for image retrieval. +* ``vocabulary``: This folder contains all the vocabulary files. + +While it's recommended to directly use the rosbag data converter to create cuVGL data format, you can also +create the map from raw images. + +To do this you must prepare the keyframe ``frames_meta.pb.txt`` metadata file +for your raw images. + +The ``frames_meta.pb.txt`` is a text ``protobuf`` file of message ``KeyframesMetadataCollection``, for the detailed +definition see the ``keyframe_metadata.pb.h`` file under the install folder of cuVGL. + +.. code-block:: bash + + cat $(ros2 pkg prefix isaac_ros_visual_mapping)/include/isaac_mapping/protos/visual/general/keyframe_metadata.pb.h + +#. Prepare a text protobuf file of message ``KeyframesMetadataCollection`` and put it under: + + .. code-block:: bash + + $MAP_FOLDER/rectified/ + image_0.jpg + image_1.jpg + ... + frames_meta.pb.txt + +#. Create the global localization map using the following command: + + .. code-block:: bash + + # Create the global localization map, it will create bow index, bow vocabulary + ros2 run isaac_ros_visual_mapping create_cuvgl_map.py --map_folder=$MAP_FOLDER --raw_image_folder=$MAP_FOLDER/rectified diff --git a/public/_sources/concepts/visual_global_localization/tutorials/tutorial_map_creation.rst.txt b/public/_sources/concepts/visual_global_localization/tutorials/tutorial_map_creation.rst.txt index 336eeae96..0f6cace02 100644 --- a/public/_sources/concepts/visual_global_localization/tutorials/tutorial_map_creation.rst.txt +++ b/public/_sources/concepts/visual_global_localization/tutorials/tutorial_map_creation.rst.txt @@ -1,123 +1,629 @@ -Tutorial: cuVGL Map Creation -============================ +.. _tutorial_map_creation: -End-to-End Visual and Occupancy Map Creation --------------------------------------------- +Tutorial: End-to-End Visual and Occupancy Map Creation +====================================================== -We provide an end-to-end script to create visual maps from ROS bags, -refer to :doc:`Tutorial: End-to-End Visual and Occupancy Map Creation `. -It outputs a cuVSLAM map, a cuVGL map, and an occupancy map in the same coordinate system. -The output maps can be used by cuVSLAM and cuVGL localization. +This tutorial describes how to create maps for visual localization including +visual global (cuVGL) localization map creation, cuVSLAM map creation, and +occupancy grid map creation. The three types of maps share the same coordinate +system. The poses from cuVGL and cuVSLAM localization align with the occupancy map. +Before starting the steps of the tutorial, read the sections as directed to learn more about concepts for your particular situation: -Create cuVGL Map Using Your Own SLAM Algorithm ----------------------------------------------- +- To understand the different types of maps generated from the workflow, read the :ref:`Map Types ` section. -If you want to use your own SLAM algorithm to create the cuVGL map, you can follow these steps: +- If you collect your own rosbag for map creation, read the following sections: -#. Collect a rosbag using appropriate data recording tools. -#. Run your own SLAM algorithm to generate the poses. -#. Export TensorRT engine files as described in :ref:`Export TensorRT Engine Files `. -#. Extract images from the rosbags. You can use the following command to extract features from rosbags. + - :ref:`Data Collection ` + - :ref:`Camera Calibration ` - Create a camera topic config that matches with your rosbag recording. + +You can use this tutorial to: + +- Create maps from an existing rosbag in the :ref:`Quick Start with an Existing Rosbag ` section. + +- Use a RealSense camera for map creation and localization, in the :ref:`Map and Localize with a RealSense ` section. + +- Verify the map quality in the :ref:`Map Quality Verification ` section. + +.. _tutorial_map_creation_map_types: + +Map Types +--------- +The following list provides examples of some of the different types of maps that are generated with +rosbags when running the :code:`create_map_offline.py` script: + +**cuVSLAM Map** + +cuVSLAM is able to create a map and load a saved map of an environment. It can then use that map to +improve localization performance and maintain a consistent global frame of reference. + + +**Visual Global Localization Map** + +During startup or after losing localization, the visual global localization map can be +used to globally localize on a previously created map and operate in a shared +global frame. + +For more info about visual global localization, refer to: :doc:`Concepts: Visual Global Localization ` + +**Occupancy Grid Map** + +Navigation packages such as `nav2 `_ use an occupancy +grid map to represent the obstacles in a map. We use :doc:`cuVSLAM `, +:doc:`Stereo Depth ` and :doc:`Nvblox ` to build an occupancy grid map from images. + +.. note:: + + - The generated occupancy map is only intended to be used for global path planning. Specifically it is not intended to be used for 2D Lidar localization. The generated map may contain slight artifacts and imprecisions and therefore is expected to be used with a planner that inflates obstacles. + + - Because the ROS2 rosbag replay is nondeterministic, each run of the occupancy map creation can produce a slightly different map. + +.. _tutorial_map_creation_data_collection: + +Data Collection +--------------- + +- Closed Loop Segments: Build mapping trajectories in loops or segments of around 5-10 meters. + This ensures that the same area is captured from different angles, which improves + map detail and reduces drift. + +- Avoid Long Straight Paths: Long drives in unexplored areas accumulate drift risk. + Use short, closed loops instead. + +- Vary Camera Angles: Capturing locations from multiple angles makes the visual map + more reliable for future localization. + +The following schematic examples show efficient mapping paths in both narrow corridors and open +spaces. They demonstrate optimal patterns for capturing comprehensive visual data +and reducing tracking drift: + +.. note:: + For optimal pose correction and map accuracy, Loop Closing must + be effectively exploited. This mechanism corrects the robot's pose when + the robot revisits a previously mapped location. +.. figure:: + :ir_lfs:`` + :width: 800px + :alt: Visualization of the mapping trajectory in corridor + :align: center +.. figure:: + :ir_lfs:`` + :width: 800px + :alt: Visualization of the mapping trajectory in open space + :align: center + +.. _tutorial_map_creation_camera_calibration: + +Camera Calibration +------------------ + +In this tutorial, "raw" means original images with distortion, and "rectified" means stereo rectified images +without distortion. + +Ensure the following topics are recorded in the rosbag: + +- static transform between base frame and camera frame. +- raw or rectified images. +- camera parameters. + +Here is an example of the left camera topic names being given image types and compression: + +.. list-table:: Left Camera Topic Names + :widths: 21 21 28 28 + :header-rows: 1 + + * - Image Type + - Camera Info + - Image + - Compressed Image + * - Raw + - `//left/camera_info` + - `//left/image_raw` + - `//left/image_raw/compressed` + * - Rectified + - `//left/camera_info_rect` + - `//left/image_rect` + - `//left/image_rect/compressed` + +Change the camera info and image topic names for the right camera by replacing "left" with "right" in the above table. + +If your rosbag topic names are different from the default ones, create a camera topic config that +matches with your rosbag recording and use it in the map creation step. For example: .. code-block:: yaml stereo_cameras: - - name: my_camera - left: /my_camera/left/image_raw - left_camera_info: /my_camera/left/camera_info - right: /my_camera/right/image_raw - right_camera_info: /my_camera/right/camera_info + - name: + left: //left/image_raw + left_frame_id: _left_optical_frame + left_camera_info: //left/camera_info + right: //right/image_raw + right_camera_info: //right/camera_info + right_frame_id: _right_optical_frame + +You must either provide stereo-rectified images or supply the stereo rectification parameters in the camera info when using raw images. + +You can use the following checks to verify that the calibration is configured correctly. + +.. tabs:: + + .. tab:: Raw Images + + - `k` and `d` correspond to the raw images. + - `r` is typically not an identity matrix, since rectification is still required. + - `k` (raw intrinsics) is typically different from the first 3x3 block in `p`, because `p` contains the rectified intrinsics. + - The first 3x3 block in `p` is the same for both left and right images, because both are projected to the same rectified image plane. + + .. tab:: Rectified Images + + - `d` is an empty or all zeros (no distortion remains after rectification). + - `k` is typically matches the first 3x3 block of `p`, since both describe the same rectified intrinsics. + - `r` depends on the `frame_id`: + + - If `frame_id` refers to rectified optical frame, `r` should be identity (no transform needed). + - If `frame_id` refers to raw optical frame, `r` is typically not identity (a transform from raw to rectified is needed). + +.. _tutorial_map_creation_set_up_development_environment: + +Set Up Development Environment +------------------------------ + +.. include:: /_snippets/set_up_dev_env.rst + +.. _tutorial_map_creation_check_gpu_memory: + +Check GPU Memory (x86 Only) +---------------------------- + +.. warning:: + + - Map creation only works with x86 laptops with NVIDIA GPU (compute_capability >= 8.0 and 8 GB RAM or higher). + + - Map Creation will use all the CPU and GPU resources, make sure you do not have anything important running at the same time. + +#. Activate the Isaac ROS environment: + + .. code:: bash + + isaac-ros activate + +#. Check GPU memory: + + Install the tool to check GPU memory inside the container: + + .. code:: bash + + pip install gpustat --break-system-packages + + Run the command to check the GPU memory: + + .. code:: bash + + gpustat + + The output will show GPU information. For example: + + .. code:: + + [0] NVIDIA RTX A6000 | 44°C, 0 % | 15 / 49140 MB | + + In this example, the GPU has 49140 MB (approximately 49 GB) of total memory. + +#. Set the model resolution environment variable based on your GPU memory: + + - For above 16 GB, set: + + .. code:: bash + + export FOUNDATIONSTEREO_MODEL_RES=high_res + + - For less than 16 GB, set: + + .. code:: bash + + export FOUNDATIONSTEREO_MODEL_RES=low_res + +.. _tutorial_map_creation_build_isaac_mapping_ros_package: + +Build |package_name| +~~~~~~~~~~~~~~~~~~~~ + +.. tabs:: + + .. tab:: Binary Package + + #. Activate the Isaac ROS environment: + + .. code:: bash + + isaac-ros activate + + #. (X86 Only) Run GPU memory check to set the environment variable for the FoundationStereo model resolution: + + .. code:: bash + + export FOUNDATIONSTEREO_MODEL_RES= + + #. Install the prebuilt Debian packages: + + :ir_apt: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-isaac-mapping-ros && \ + sudo apt-get install -y ros-:ir_ros_distro:-isaac-ros-foundationstereo-models-install + + #. Download and install the FoundationStereo model files: + + .. code:: bash + + ros2 run isaac_ros_foundationstereo_models_install install_foundationstereo_models.sh --eula \ + --model_res ${FOUNDATIONSTEREO_MODEL_RES} + + .. tab:: Build from Source + + #. Install Git LFS: + + .. code:: bash + + sudo apt-get install -y git-lfs && git lfs install + + #. Clone this repository under ``${ISAAC_ROS_WS}/src``: + + .. code:: bash + + cd ${ISAAC_ROS_WS}/src && \ + git clone :ir_clone:`` - .. code-block:: bash + #. Activate the Isaac ROS environment: - # Set following variables to your own paths - SENSOR_DATA_BAG="path_to_sensor_data.bag" - POSE_BAG="path_to_pose.bag" - MAP_FOLDER="path_to_map_folder" - POSE_TOPIC_NAME="topic_name_of_the_pose" - CAMERA_TOPIC_CONFIG="path_to_camera_topic_config.yaml" + .. code:: bash - # Then extract the keyframes with image features from the rosbag - ros2 run isaac_mapping_ros rosbag_to_mapping_data \ - --sensor_data_bag_file=$SENSOR_DATA_BAG \ - --pose_bag_file=$POSE_BAG \ - --output_folder_path="$MAP_FOLDER/raw" \ - --min_inter_frame_rotation_degrees=5 \ - --min_inter_frame_distance=0.2 \ - --pose_topic_name=$POSE_TOPIC_NAME \ - --camera_topic_config=$CAMERA_TOPIC_CONFIG + isaac-ros activate - .. note:: - * Only ``geometry_msgs/msg/PoseStamped``, ``geometry_msgs/msg/PoseWithCovarianceStamped``, ``nav_msgs/msg/Odometry``, and ``nav_msgs/msg/Path`` message types are supported for pose type in the pose rosbag. Poses stored in the pose bag are in ``base_link`` frame. - * Change ``--min_inter_frame_rotation_degrees`` and ``--min_inter_frame_distance`` to your own values for proper density of the keyframes. Larger environments might require larger values. + #. (X86 Only) Run GPU memory check to set the environment variable for the FoundationStereo model resolution: - More documentation about the ``rosbag_to_mapping_data`` tool can be found in the :doc:`isaac_mapping_ros documentation `. + .. code:: bash -#. Create cuVGL map with following command: + export FOUNDATIONSTEREO_MODEL_RES= - .. code-block:: bash + #. Use ``rosdep`` to install the package's dependencies: + :ir_apt: - # Create the global localization map, it will create bow index, bow vocabulary - ros2 run isaac_ros_visual_mapping create_cuvgl_map.py --map_folder=$MAP_FOLDER \ - --binary_folder_path $(ros2 pkg prefix isaac_ros_visual_mapping)/bin/visual_mapping \ - --config_folder_path $(ros2 pkg prefix --share isaac_ros_visual_mapping)/configs/isaac/ \ - --model_dir $(ros2 pkg prefix --share isaac_ros_visual_mapping)/models/ + .. code:: bash - .. note:: - * If you export the TensorRT engine files, pass ``--model_dir $OUTPUT_MODEL_DIR`` when running ``create_cuvgl_map.py``. - * If you have a prebuilt vocabulary, pass ``--prebuilt_bow_vocabulary_folder `` when running ``create_cuvgl_map.py``. For example: + rosdep update && rosdep install --from-paths ${ISAAC_ROS_WS}/src/isaac_ros_mapping_and_localization/isaac_mapping_ros --ignore-src -y + + #. Download and install the FoundationStereo model files: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-isaac-ros-foundationstereo-models-install && \ + ros2 run isaac_ros_foundationstereo_models_install install_foundationstereo_models.sh --eula \ + --model_res ${FOUNDATIONSTEREO_MODEL_RES} + + #. Build the package from source: + + .. code:: bash + + cd ${ISAAC_ROS_WS} && \ + colcon build --symlink-install --packages-up-to isaac_mapping_ros --base-paths ${ISAAC_ROS_WS}/src/isaac_ros_mapping_and_localization/isaac_mapping_ros + + #. Source the ROS workspace: + + .. note:: + + Make sure to repeat this step in **every** terminal created inside the Isaac ROS environment. + + Because this package was built from source, the enclosing workspace must be sourced for ROS to be able to find the package's contents. + + .. code:: bash + + source install/setup.bash + + +.. |package_name| replace:: ``isaac_mapping_ros`` + +.. _tutorial_map_creation_quick_start_existing_rosbag: + +Quick Start with an Existing Rosbag +----------------------------------- + +.. note:: + Make sure that the rosbag and output map folder path are mounted to the Isaac ROS environment. + You can add them in ``~/.isaac_ros_dev-dockerargs`` then restart the Isaac ROS environment. + +#. Download the ``r2b_galileo`` dataset from the + `r2b 2024 dataset on NGC `__. + It is a 20-second rosbag containing synchronized images from four stereo camera pairs. + +#. Open a terminal and activate the Isaac ROS environment: + + .. code:: bash + + isaac-ros activate + +#. (X86 Only) Run GPU memory check to set the environment variable for the FoundationStereo model resolution: + + .. code:: bash + + export FOUNDATIONSTEREO_MODEL_RES= + +#. Create the maps mentioned above using the following command: + + .. code:: bash + + ros2 run isaac_mapping_ros create_map_offline.py \ + --sensor_data_bag= \ + --base_output_folder= \ + --fs_model_res=${FOUNDATIONSTEREO_MODEL_RES} + +After successful completion, verify that you see a message confirming that maps have +been created. The full logs for each step are stored in the outputs. All steps include: + +- `Extract edex` step extracts RGB images and metadata from rosbag. +- `Create cuVSLAM map` step computes the cuVSLAM pose and map. +- `Optimize odometry pose with keyframe pose` step processes the odometry pose and loop closures computed by cuVSLAM and outputs more accurate odometry poses. +- `Update frame metadata pose` step updates the image metadata with the computed poses. +- `Select map frames` step samples key frames using a translation and rotation distance from all images. +- `Copy map frames` step copies the sampled keyframes to a keyframe folder. +- `Run Foundation Stereo inference` step runs Foundation Stereo inference on keyframes and outputs depth images. +- `Run Nvblox` step creates a 2D occupancy map from keyframes using RGB+depth images and poses. +- `Extract features` step extracts ``ALIKED`` image features for keyframes. +- `Build vocabulary` step builds a visual vocabulary from extracted features. +- `Build BoW index` step builds a bag-of-words image retrieval database from extracted features, which together with vocabulary form the global localization map. + +Verify `occupancy_map.png` file in the output map folder: + +.. figure:: + :ir_lfs:`` + :width: 800px + :alt: r2b_galileo_omap + :align: center + +.. _tutorial_map_creation_map_and_localize_with_a_realsense: + +Map and Localize with a RealSense +--------------------------------- + +.. warning:: + + - Mapping workflow works best in closed, structured indoor spaces with nearby visual features. In more open environments or scenes with far backgrounds, mapping accuracy can degrade due to fewer constraints. + + - Glass and very thin structures such as wires and cable railings cannot be detected by the current stereo networks used for depth estimation. If you have such structures in your environment, you might need to modify the environment so that they are more visible features, to have the unnavigable areas correctly estimated. + + - The quality of the occupancy map is dependent on the disparity data provided to Nvblox. Degraded results can occur for wall corners. Improved results might be achieved with alternative stereo modalities, such as a different stereo camera or other AI/DNNs for stereo disparity estimation. + +You can use a RealSense D435i camera for following the steps below. + +Activate the Isaac ROS environment for every new terminal created when running the following steps +by running the command ``isaac-ros activate`` in the terminal. + +#. Set up the development environment by following :ref:`Set Up Development Environment ` + instructions. + +#. Build the package by following :ref:`Build Isaac Mapping ROS Package ` + instructions. + +#. Set up the RealSense camera by following the :doc:`RealSense Setup ` instructions. + Plug in the camera and run the command ``rs-enumerate-devices -S`` in the terminal to check the + camera model. For example: + + .. code:: bash + + Device Name Serial Number Firmware Version + Intel RealSense D435I 337122071493 5.16.0.1 + +#. Set up visualization. + + #. Follow the :ref:`Foxglove setup ` guide to launch Foxglove. + + #. Download Foxglove layout file from + :ir_repo:`localize_realsense.json `. + + #. Import the downloaded layout file into Foxglove. + +#. Run a quick check on cuVSLAM result with RealSense camera. + + #. Open a terminal and activate the Isaac ROS environment: .. code-block:: bash - ros2 run isaac_ros_visual_mapping create_cuvgl_map.py --map_folder=$MAP_FOLDER --prebuilt_bow_vocabulary_folder= + isaac-ros activate + #. Launch the RealSense camera with cuVSLAM node. -Create cuVGL Map From Images ----------------------------- + .. code-block:: bash + + ros2 launch isaac_mapping_ros localize_realsense.launch.py enable_vgl:=False + + #. Move the camera forward by 1m, and verify the cuVSLAM reports a translation of + around ``[1.0, 0.0, 0.0]`` in the Foxglove panel. If the reported + odometry measurement is inaccurate, make sure the environment has + sufficient near-distance objects for feature tracking, and verify + the camera calibration is correct. + +#. Record a rosbag for map creation. + + #. Launch the RealSense camera: + + .. code-block:: bash + + ros2 launch isaac_mapping_ros localize_realsense.launch.py \ + enable_vslam:=False \ + enable_vgl:=False + + #. In a new terminal, activate the Isaac ROS environment + + .. code-block:: bash + + isaac-ros activate + + Then, start rosbag recording: + + .. code-block:: bash + + ros2 bag record \ + /tf_static \ + /realsense/left/camera_info_rect \ + /realsense/left/image_rect \ + /realsense/right/camera_info_rect \ + /realsense/right/image_rect \ + --storage mcap \ + -o + + #. Collect data following the :ref:`Data Collection ` guidelines. + Additionally, follow these recommendations for handheld mapping bags: + + - Hold the camera in the correct orientation. For the Intel RealSense Depth Camera D435i, + the screw hole should face downward while recording. + + - Record in areas with sufficient nearby visual features. Avoid scenes dominated by distant + backgrounds. + + - Avoid sudden or sharp motions. Keep the camera facing forward, and rotate it smoothly when + looking up, down, or around. + + - Start and stop recording at approximately the same pose to help ensure loop closure. + + - Move the camera close to the objects you want to map, including the ground and surrounding + structures. + + An example of a recording captured around a cafe table area: + + .. figure:: + :ir_lfs:`` + :width: 800px + :alt: Cafe Table Area + :align: center + + #. After data collection is finished, use ``ctrl+c`` to stop the rosbag recording + and camera driver. Verify the rosbag contains all the topics listed above + by running the command ``ros2 bag info ``. + +#. (X86 Only) Run GPU memory check to set the environment variable for the FoundationStereo model resolution: + + .. code:: bash + + export FOUNDATIONSTEREO_MODEL_RES= + +#. Create maps for the RealSense rosbag using the following command: + + .. code-block:: bash + + ros2 run isaac_mapping_ros create_map_offline.py \ + --sensor_data_bag= \ + --base_output_folder= \ + --camera_topic_config=$(ros2 pkg prefix isaac_mapping_ros --share)/configs/data_converter_realsense.yaml \ + --base_link_name=camera_link \ + --fs_model_res=${FOUNDATIONSTEREO_MODEL_RES} + + The ``--base_link_name`` is used to specify the TF frame name in your rosbag. + The ``--camera_topic_config`` is used to specify the YAML file for the custom + camera topic, camera info topic, and camera frame names. + +#. Verify the map quality by referring to the + :ref:`Map Quality Verification ` + section. + +#. Export the TensorRT engine file as described in + :ref:`Export TensorRT Engine Files `. + +#. Run live localization using the maps generated above: + + .. code-block:: bash + + ros2 launch isaac_mapping_ros localize_realsense.launch.py \ + map_dir:= \ + vgl_model_dir:= + + It starts the RealSense camera, cuVSLAM and cuVGL nodes, and an + occupancy map server. + + The cuVGL node first computes a global localization pose + for cuVSLAM to bootstrap localization. After cuVSLAM successfully localizes + in the map, cuVGL stops localization and cuVSLAM continuously tracks features + and performs optimization with the map. + +#. To run localization with a pre-recorded rosbag, specify the rosbag path + in the launch file: + + .. code-block:: bash + + ros2 launch isaac_mapping_ros localize_realsense.launch.py \ + map_dir:= \ + vgl_model_dir:= \ + rosbag:= + + Replay is at real time by default. You can adjust the replay rate by + ``replay_rate:=``. When running a short localization bag, + use ``replay_rate:=0.1`` to slow down the replay, allowing more + localization triggers and increasing the chances of successful localization. + +.. _tutorial_map_creation_map_quality_verification: + +Map Quality Verification +------------------------ + +Pose Plot +~~~~~~~~~ + +Pose trajectory plots are saved under `pose_comparison` folder. -The map creation process in cuVGL requires two inputs: +.. figure:: + :ir_lfs:`` + :width: 800px + :alt: Pose Comparison + :align: center -* Rectified Images (From stereo camera) -* Poses +The plots show the final poses used for map creation in ``XY`` and ``XZ`` planes. +The green circle represents the start pose, and the +red square represents the end pose. -cuVGL extracts features from the images and saves them along with the corresponding poses. -The cuVGL map is structured as a folder that contains the following files: +If data collection starts and ends at approximately the same pose, the distance +between the green circle and the red square represents the pose drifts during mapping. -* ``keyframes``: This folder contains the features extracted from the raw images, with each individual keyframe saved as a binary protobuf file. -* ``keyframes/frames_meta.pb.txt``: This ``protobuf`` file contains metadata for the keyframes including timestamp, poses, and ``image_name``. -* ``bow_index.pb``: This is the bag-of-words index file for image retrieval. -* ``vocabulary``: This folder contains all the vocabulary files. +- If you observe noticeable separation between the start and end poses (loop-closure drift), + recollect the data in a closed loop and enable multiple passes by setting ``-o cuvslam.repeat=2`` + in the map creation command. -While it's recommended to directly use the rosbag data converter to create cuVGL data format, you can also -create the map from raw images. +Occupancy Map +~~~~~~~~~~~~~ -To do this you must prepare the keyframe ``frames_meta.pb.txt`` metadata file -for your raw images. +The 2D occupancy map is saved to `occupancy_map.png` and `occupancy_map.yaml` +in the output map folder. A good occupancy map should have well-aligned objects +and walls, for example: -The ``frames_meta.pb.txt`` is a text ``protobuf`` file of message ``KeyframesMetadataCollection``, for the detailed -definition see the ``keyframe_metadata.pb.h`` file under the install folder of cuVGL. +.. figure:: + :ir_lfs:`` + :width: 800px + :alt: Good OMap + :align: center -.. code-block:: bash +A **bad** occupancy map can have noisy artifacts or misaligned walls, like this: - cat $(ros2 pkg prefix isaac_ros_visual_mapping)/include/isaac_mapping/protos/visual/general/keyframe_metadata.pb.h +.. figure:: + :ir_lfs:`` + :width: 800px + :alt: OMap poor quality + :align: center -#. Prepare a text protobuf file of message ``KeyframesMetadataCollection`` and put it under: - .. code-block:: bash +- You can include objects that are farther away in the occupancy map by increasing the + Nvblox integration distance using the + ``-o nvblox.projective_integrator_max_integration_distance_m=`` + flag in the map creation command. - $MAP_FOLDER/rectified/ - image_0.jpg - image_1.jpg - ... - frames_meta.pb.txt +Overriding Parameters +~~~~~~~~~~~~~~~~~~~~~ -#. Create the global localization map using the following command: +The map creation configuration is defined in :ir_repo:`map_creation_config.yaml `. +You can override the cuVSLAM and Nvblox parameters using one of the following methods: - .. code-block:: bash +- Pass the overrides as command line arguments, for example: ``-o cuvslam.repeat=2 -o nvblox.projective_integrator_max_integration_distance_m=3.5``. - # Create the global localization map, it will create bow index, bow vocabulary - ros2 run isaac_ros_visual_mapping create_cuvgl_map.py --map_folder=$MAP_FOLDER --raw_image_folder=$MAP_FOLDER/rectified +- Create a custom config file by copying the default config file from + :ir_repo:`map_creation_config.yaml ` + and modify the parameters you want to change. Then pass it when running map creation with the ``--map_creation_config=`` flag. \ No newline at end of file diff --git a/public/_sources/getting_started/compute/preempt_setup.rst.txt b/public/_sources/getting_started/compute/preempt_setup.rst.txt index 83537ad6d..ffe03c71a 100644 --- a/public/_sources/getting_started/compute/preempt_setup.rst.txt +++ b/public/_sources/getting_started/compute/preempt_setup.rst.txt @@ -2,12 +2,12 @@ PREEMPT_RT Kernel for Jetson ============================ -We provide a PREEMPT_RT kernel for ``Jetpack 7.0``. This kernel is recommended only for use with robot manipulators, as many manipulator manufacturers recommend a low-latency kernel for interfacing with their robots. +We provide a PREEMPT_RT kernel for ``Jetpack 7.1``. This kernel is recommended only for use with robot manipulators, as many manipulator manufacturers recommend a low-latency kernel for interfacing with their robots. Install PREEMPT_RT kernel from apt server ------------------------------------------- -1. Follow instructions from `Developer guide `__ +1. Follow instructions from `Developer guide `__ to install PREEMPT_RT kernel on Jetson. 2. Check if PREEMPT_RT kernel is active by running the below command which should return text that contains ``PREEMPT RT``. diff --git a/public/_sources/getting_started/index.rst.txt b/public/_sources/getting_started/index.rst.txt index 7db16bf4f..a66102836 100644 --- a/public/_sources/getting_started/index.rst.txt +++ b/public/_sources/getting_started/index.rst.txt @@ -49,15 +49,15 @@ Initialize Compute #. After boot, confirm that you have installed the correct version of ``Jetpack`` by running the following command. Confirm that the output has the terms - ``R38 (release), REVISION: 2.2``. + ``R38 (release), REVISION: 4.0``. .. code:: bash cat /etc/nv_tegra_release - #. Set the power mode to ``MAXN`` using `this guide `__. + #. Set the power mode to ``MAXN`` using `this guide `__. - #. Set the GPU and CPU clock speeds to max using `this guide `__. + #. Set the GPU and CPU clock speeds to max using `this guide `__. #. Add your user to the ``docker`` group. @@ -75,6 +75,20 @@ Initialize Compute - :doc:`Jetson Storage Setup ` - :doc:`Preempt Setup ` + .. tab-item:: DGX Spark Platforms + :sync: dgx_spark + + #. Add your user to the ``docker`` group. + + .. code:: bash + + sudo usermod -aG docker $USER + newgrp docker + + #. Setup Docker. + + .. include:: /_snippets/docker_buildx.rst + Create a Workspace ------------------ @@ -104,6 +118,17 @@ Create a Workspace echo 'export ISAAC_ROS_WS="${ISAAC_ROS_WS:-/mnt/nova_ssd/workspaces/isaac_ros-dev/}"' >> ~/.bashrc source ~/.bashrc + .. tab-item:: DGX Spark Platforms + :sync: dgx_spark + + Create a ROS 2 workspace for experimenting with Isaac ROS: + + .. code:: bash + + mkdir -p ~/workspaces/isaac_ros-dev/src + echo 'export ISAAC_ROS_WS="${ISAAC_ROS_WS:-${HOME}/workspaces/isaac_ros-dev/}"' >> ~/.bashrc + source ~/.bashrc + Configure Isaac ROS Apt Repository ---------------------------------- diff --git a/public/_sources/getting_started/sensors/index.rst.txt b/public/_sources/getting_started/sensors/index.rst.txt index 668c60891..718ae1dff 100644 --- a/public/_sources/getting_started/sensors/index.rst.txt +++ b/public/_sources/getting_started/sensors/index.rst.txt @@ -3,6 +3,10 @@ Sensors Setup Isaac ROS officially supports RealSense and ZED Cameras. +.. note:: + + Argus has not been tested on Jetson AGX Thor and is not supported at this time. + Configure one or more of the cameras: diff --git a/public/_sources/performance/index.rst.txt b/public/_sources/performance/index.rst.txt index 7c1e25828..6d4b13774 100644 --- a/public/_sources/performance/index.rst.txt +++ b/public/_sources/performance/index.rst.txt @@ -8,8 +8,6 @@ The performance results of benchmarking the Isaac ROS packages on both Jetson an .. include:: tables/isaac_ros_graphs.rst -.. include:: tables/isaac_ros_live_graphs.rst - Methodology ----------- diff --git a/public/_sources/reference_workflows/isaac_for_manipulation/packages/isaac_manipulator_ur_dnn_policy/index.rst.txt b/public/_sources/reference_workflows/isaac_for_manipulation/packages/isaac_manipulator_ur_dnn_policy/index.rst.txt index c2ba7be4c..da5e82836 100644 --- a/public/_sources/reference_workflows/isaac_for_manipulation/packages/isaac_manipulator_ur_dnn_policy/index.rst.txt +++ b/public/_sources/reference_workflows/isaac_for_manipulation/packages/isaac_manipulator_ur_dnn_policy/index.rst.txt @@ -48,16 +48,6 @@ Download Quickstart Assets :ir_assets:` ` -Install Python Dependencies -~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -Install RSL-RL: - -.. code:: bash - - sudo apt-get install -y python3-git \ - && pip install --break-system-packages tensordict \ - && pip install --break-system-packages --no-deps rsl-rl-lib==3.1.1 Build |package_name| ~~~~~~~~~~~~~~~~~~~~ diff --git a/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/pick_and_place/tutorial_pick_and_place.rst.txt b/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/pick_and_place/tutorial_pick_and_place.rst.txt index 0eb42c48b..ef332ac27 100644 --- a/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/pick_and_place/tutorial_pick_and_place.rst.txt +++ b/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/pick_and_place/tutorial_pick_and_place.rst.txt @@ -475,7 +475,7 @@ Configure the Workflow # The user can run nvblox with FoundationStereo by enabling nvblox but the environment representation can be old (since the FoundationStereo model can take over 1-2 seconds to generate a depth image) # Foundation Stereo configuration - foundation_stereo_engine_file_path: '${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_320x736.engine' + foundation_stereo_engine_file_path: '${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_320x736.engine' # Static planning scene configuration moveit_collision_objects_scene_file: '' diff --git a/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/sim_to_real/tutorial_sim_to_real.rst.txt b/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/sim_to_real/tutorial_sim_to_real.rst.txt index f35a7b26d..3f6a85109 100644 --- a/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/sim_to_real/tutorial_sim_to_real.rst.txt +++ b/public/_sources/reference_workflows/isaac_for_manipulation/tutorials/sim_to_real/tutorial_sim_to_real.rst.txt @@ -47,14 +47,6 @@ Deploy the Policy using Isaac ROS #. Set up your development environment using the instructions in :doc:`getting started `. -#. Install ``RSL-RL``: - - .. code:: bash - - sudo apt-get install -y python3-git \ - && pip install --break-system-packages tensordict \ - && pip install --break-system-packages --no-deps rsl-rl-lib==3.1.2 - #. Install ``isaac_manipulator_ur_dnn_policy`` .. tabs:: diff --git a/public/_sources/releases/index.rst.txt b/public/_sources/releases/index.rst.txt index ee0302b30..4232ab43f 100644 --- a/public/_sources/releases/index.rst.txt +++ b/public/_sources/releases/index.rst.txt @@ -2,8 +2,35 @@ Release Notes ============= -Isaac ROS 4.1.0 February 2, 2026 --------------------------------- +Isaac ROS 4.2.0 :ir_release_date:`<4.2.0>` +------------------------------------------ + +Packages available as `4.2.0 Release` tagged `v4.2.0` on GitHub. + +What's New +~~~~~~~~~~ + +Updates including: + +- Support for DGX Spark +- Support for JetPack 7.1 +- Support for Thor T4000 SKU +- ``isaac_ros_dnn_stereo_depth``: Add support for `FoundationStereo v2 `__ +- ``isaac_manipulator``: New sim-to-real tutorial for gear assembly insertion policy on UR10e +- ``isaac_mapping_ros``: Support for visual map creation and localization with hand-held camera + +Limitations +~~~~~~~~~~~ + +This release has the following known limitations, with workarounds available in the troubleshooting section: + +- The Mission Dispatch and Mission Database containers are not yet supported on DGX Spark +- RealSense cameras are not yet supported on DGX Spark due to SDK and kernel compatibility issues +- ``isaac_mapping_ros``: r2b dataset used in map creation tutorial is for map validation only; localization examples are not provided for this sample + + +Isaac ROS 4.1.0 :ir_release_date:`<4.1.0>` +------------------------------------------ Packages available as `4.1.0 Release` tagged `v4.1.0` on GitHub. @@ -12,7 +39,7 @@ What's New Updates including: -- Added support for two new Docker-optional development and deployment modes: Virtual Environment and Bare Metal +- Added support for two new Docker-optional development and deployment modes: Virtual Environment and Bare Metal - ``isaac_ros_nvblox``: New dynamics support for Lidar and Lidar motion compensation - ``sensor_mounting_rig``: Support for Jetson AGX Thor RealSense Rig - ``isaac_ros_visual_slam``: Support for ``RGBD`` cameras (`isaac_ros_visual_slam #138 `__) @@ -28,7 +55,7 @@ This release has the following known limitations, with workarounds available in - FoundationStereo model conversion in ``fp16`` can cause an Out-of-Memory error due to a limitation in the version of TensorRT used by Isaac ROS - The PyTorch backend of the Triton Inference Server is not supported. `(nvbugs/5737017)` - The SAM2 visualization script may fail due to a ``numpy`` mismatch when doing the Virtual Environment flow. Downgrading ``numpy`` to ``1.26.4`` may fix this issue. `(nvbugs/5851967)` -- The DOPE quickstart will fail on Jetson AGX Thor when converting from an ONNX model to a TensorRT Plan file due to unsupported layers. `(nvbugs/5548869)` +- The DOPE quickstart will fail on Jetson AGX Thor when converting from an ONNX model to a TensorRT Plan file due to unsupported layers. `(nvbugs/5548869)` Issues Addressed ~~~~~~~~~~~~~~~~ @@ -37,8 +64,8 @@ This release has fixed the following known issues: - Stability issues for RealSense SDK support for JetPack 7 can be resolved by following :doc:`RealSense setup tutorial `. `(nvbugs/5561995)` -Isaac ROS 4.0 Update 1 December 10, 2025 ----------------------------------------- +Isaac ROS 4.0 Update 1 :ir_release_date:`<4.0-1>` +------------------------------------------------- Packages available as `4.0 Update 1` tagged `v4.0-1` on GitHub. @@ -52,8 +79,8 @@ Updates including: - ``isaac_ros_rtdetr``: Support third party RT-DETR models - ``isaac_ros_common``: Correct asset installation path inside Debian packages -Isaac ROS 4.0.0 October 24, 2025 --------------------------------- +Isaac ROS 4.0.0 :ir_release_date:`<4.0.0>` +------------------------------------------ Packages available as `4.0.0 Release` tagged `v4.0.0` on GitHub. @@ -98,8 +125,8 @@ Contributions - `isaac_ros_apriltag PR #64 `__: Fix TF broadcasting for the detected AprilTags -Isaac ROS 3.2 Update 15 December 10, 2025 ------------------------------------------ +Isaac ROS 3.2 Update 15 :ir_release_date:`<3.2-15>` +--------------------------------------------------- Packages available as `3.2 Update 15` tagged `v3.2-15` on GitHub. @@ -111,8 +138,8 @@ Updates including: - ``isaac_perceptor``: Fix ``rosdep install`` to scan entire workspace and ensure all dependencies are installed - ``isaac_ros_common``: Update Perceptor asset tarballs for TensorRT 10.3 -Isaac ROS 3.2 Update 14 November 12, 2025 ------------------------------------------ +Isaac ROS 3.2 Update 14 :ir_release_date:`<3.2-14>` +--------------------------------------------------- Packages available as `3.2 Update 14` tagged `v3.2-14` on GitHub. @@ -126,8 +153,8 @@ Updates including: - ``isaac_ros_pose_estimation``: Enhance FoundationPose dynamic mesh reloading support -Isaac ROS 3.2 Update 13 October 8, 2025 ---------------------------------------- +Isaac ROS 3.2 Update 13 :ir_release_date:`<3.2-13>` +--------------------------------------------------- Packages available as `3.2 Update 13` tagged `v3.2-13` on GitHub. @@ -145,8 +172,8 @@ Updates including: - ``nova_carter_bringup``: Fix boolean parameter being incorrectly parsed as a string - ``nova_developer_kit_bringup``: Improve robustness for dry run launch tests -Isaac ROS 3.2 Update 12 July 24, 2025 -------------------------------------- +Isaac ROS 3.2 Update 12 :ir_release_date:`<3.2-12>` +--------------------------------------------------- Packages available as `3.2 Update 12` tagged `v3.2-12` on GitHub. @@ -158,8 +185,8 @@ Updates including: - Update build instructions for docking with Nova Carter. - ``ros2_benchmark``: Clean up lint issues -Isaac ROS 3.2 Update 11 July 10, 2025 -------------------------------------- +Isaac ROS 3.2 Update 11 :ir_release_date:`<3.2-11>` +--------------------------------------------------- Packages available as `3.2 Update 11` tagged `v3.2-11` on GitHub. @@ -173,8 +200,8 @@ This release contains fixes to address user feedback, including: `isaac_ros_argus_camera #51 `__: Fix segmentation fault in ``isaac_ros_argus_camera`` that can occur when camera EEPROM data is in an unexpected format, corrupted, or otherwise unavailable -Isaac ROS 3.2 Update 10 July 3, 2025 ------------------------------------- +Isaac ROS 3.2 Update 10 :ir_release_date:`<3.2-10>` +--------------------------------------------------- Packages available as `3.2 Update 10` tagged `v3.2-10` on GitHub. @@ -190,8 +217,8 @@ Updates including: - ``isaac_ros_mission_client``: Update default Nav2 parameters in config for Mission Client - ``isaac_ros_nova``, ``nova_carter``: Improve Lichtblick build robustness using NVIDIA-hosted mirror -Isaac ROS 3.2 Update 9 June 13, 2025 ------------------------------------- +Isaac ROS 3.2 Update 9 :ir_release_date:`<3.2-9>` +------------------------------------------------- Packages available as `3.2 Update 9` tagged `v3.2-9` on GitHub. @@ -202,8 +229,8 @@ Updates including: - ``isaac_ros_common``: Refresh ROS apt repository key due to `OSRA key expiry `__ -Isaac ROS 3.2 Update 8 May 14, 2025 ------------------------------------ +Isaac ROS 3.2 Update 8 :ir_release_date:`<3.2-8>` +------------------------------------------------- Packages available as `3.2 Update 8` tagged `v3.2-8` on GitHub. @@ -215,8 +242,8 @@ Updates including: - ``isaac_perceptor``: Introduce new reference architecture documentation - ``isaac_ros_common``: Improve container security and image build robustness -Isaac ROS 3.2 Update 7 May 8, 2025 ----------------------------------- +Isaac ROS 3.2 Update 7 :ir_release_date:`<3.2-7>` +------------------------------------------------- Packages available as `3.2 Update 7` tagged `v3.2-7` on GitHub. @@ -229,8 +256,8 @@ Updates including: - ``isaac_ros_visual_global_localization``: Update API documentation - ``ros2_benchmark``: Update quickstart documentation -Isaac ROS 3.2 Update 6 April 3, 2025 ------------------------------------- +Isaac ROS 3.2 Update 6 :ir_release_date:`<3.2-6>` +------------------------------------------------- Packages available as `3.2 Update 6` tagged `v3.2-6` on GitHub. @@ -241,8 +268,8 @@ Updates including: - ``isaac_ros_mission_client``, ``nova_carter``: Integrated the Nova Carter navigation stack with the Mega Omniverse Blueprint -Isaac ROS 3.2 Update 5 February 27, 2025 ----------------------------------------- +Isaac ROS 3.2 Update 5 :ir_release_date:`<3.2-5>` +------------------------------------------------- Packages available as `3.2 Update 5` tagged `v3.2-5` on GitHub. @@ -258,8 +285,8 @@ Updates including: - ``ros2_benchmark``: Improved robustness of fps calculation -Isaac ROS 3.2 Update 4 February 13, 2025 ----------------------------------------- +Isaac ROS 3.2 Update 4 :ir_release_date:`<3.2-4>` +------------------------------------------------- Packages available as `3.2 Update 4` tagged `v3.2-4` on GitHub. @@ -272,8 +299,8 @@ This release contains fixes to address user feedback, including: -Isaac ROS 3.2 Update 3 February 6, 2025 ---------------------------------------- +Isaac ROS 3.2 Update 3 :ir_release_date:`<3.2-3>` +------------------------------------------------- Packages available as `3.2 Update 3` tagged `v3.2-3` on GitHub. @@ -285,8 +312,8 @@ Updates including: - support for Isaac Sim 4.5 -Isaac ROS 3.2 Update 2 January 30, 2025 ---------------------------------------- +Isaac ROS 3.2 Update 2 :ir_release_date:`<3.2-2>` +------------------------------------------------- Packages available as `3.2 Update 2` tagged `v3.2-2` on GitHub. @@ -301,8 +328,8 @@ Updates including: - ``isaac_ros_visual_slam``: Reduced image buffer size -Isaac ROS 3.2 Update 1 January 16, 2025 ----------------------------------------- +Isaac ROS 3.2 Update 1 :ir_release_date:`<3.2-1>` +------------------------------------------------- Packages available as `3.2 Update 1` tagged `v3.2-1` on GitHub. @@ -316,8 +343,8 @@ Updates including: - ``isaac_ros_common``: Update build tools installation -Isaac ROS 3.2 December 10, 2024 -------------------------------- +Isaac ROS 3.2 :ir_release_date:`<3.2>` +-------------------------------------- Packages available as `3.2 Release` tagged `v3.2` on GitHub. @@ -353,8 +380,8 @@ This release has the following known limitations, with workarounds available in - Isaac Perceptor during startup may hang due to camera drop frames. Restart the launch file to recover. -Isaac ROS 3.1 September 26, 2024 --------------------------------- +Isaac ROS 3.1 :ir_release_date:`<3.1>` +-------------------------------------- Packages available as `3.1 Release` tagged `v3.1` on GitHub. @@ -376,8 +403,8 @@ This release has the following known limitations, with workarounds available in -Isaac ROS 3.0.1 June 14, 2024 ------------------------------ +Isaac ROS 3.0.1 :ir_release_date:`<3.0.1>` +------------------------------------------ Packages available as `3.0.1 Release` tagged `v3.0.1` on GitHub. @@ -399,8 +426,8 @@ This release has the following known limitations, with workarounds available in -Isaac ROS 3.0.0 May 30, 2024 ----------------------------- +Isaac ROS 3.0.0 :ir_release_date:`<3.0.0>` +------------------------------------------ Packages available as `3.0.0 Release` tagged `v3.0.0` on GitHub. @@ -455,8 +482,8 @@ This release contains new features and fixes to address user feedback, including -Isaac ROS 2.1.0 November 16, 2023 ---------------------------------- +Isaac ROS 2.1.0 :ir_release_date:`<2.1.0>` +------------------------------------------ Packages available as `2.1.0 Release` tagged `v2.1.0` on GitHub. @@ -485,8 +512,8 @@ This release contains new features and fixes to address user feedback, including - `gxf #2 `__: Added additional files -Isaac ROS 2.0.0 October 18, 2023 --------------------------------- +Isaac ROS 2.0.0 :ir_release_date:`<2.0.0>` +------------------------------------------ Packages available as `2.0.0 Release` tagged `v2.0.0` on GitHub. diff --git a/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_decoder/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_decoder/index.rst.txt index 5b62980c7..0b4d06546 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_decoder/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_decoder/index.rst.txt @@ -188,6 +188,26 @@ can not decode P-frames until it has received the first I-frame. You can start the decoder before playing the rosbag to avoid these errors. +Symptom +^^^^^^^ + +On DGX Spark, the H.264 encoder and decoder nodes may fail to launch with the +following error: + +.. code:: bash + + Error: libnvbufsurface.so.1.0.0: cannot open shared object file: No such file or directory + +Solution +^^^^^^^^ + +This will be fixed in a future release. As a workaround, set the following +environment variable before launching the node: + +.. code:: bash + + export LD_LIBRARY_PATH="/usr/lib/aarch64-linux-gnu/nvidia:${LD_LIBRARY_PATH}" + API ---- diff --git a/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_encoder/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_encoder/index.rst.txt index 655674394..a15823c79 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_encoder/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_compression/isaac_ros_h264_encoder/index.rst.txt @@ -197,6 +197,32 @@ Visualize Results ros2 run rqt_image_view rqt_image_view /right/image_uncompressed +Troubleshooting +--------------- + +H.264 Encode/Decode May Fail on DGX Spark +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Symptom +""""""" + +On DGX Spark, the H.264 encoder and decoder nodes may fail to launch with the +following error: + +.. code:: bash + + Error: libnvbufsurface.so.1.0.0: cannot open shared object file: No such file or directory + +Solution +"""""""" + +This will be fixed in a future release. As a workaround, set the following +environment variable before launching the node: + +.. code:: bash + + export LD_LIBRARY_PATH="/usr/lib/aarch64-linux-gnu/nvidia:${LD_LIBRARY_PATH}" + API ---- diff --git a/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_ess/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_ess/index.rst.txt index 230f36ea4..b6d722d11 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_ess/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_ess/index.rst.txt @@ -240,6 +240,12 @@ Visualize Output isaac-ros activate + #. Install ``cv_bridge``: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-cv-bridge + #. In the **terminal**, visualize and validate the disparity output using the visualizer script: .. code:: bash diff --git a/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_foundationstereo/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_foundationstereo/index.rst.txt index 048110196..19f484377 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_foundationstereo/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_dnn_stereo_depth/isaac_ros_foundationstereo/index.rst.txt @@ -61,6 +61,8 @@ Build |package_name| environment variable. Use the ``--model_res`` argument to override the default or to explicitly select between these options. + The ``high_res`` (576x960) model requires more than 16GB of VRAM, so it only works on GPUs with more than 16GB of VRAM. + .. tab:: Build from Source #. Install Git LFS: @@ -109,6 +111,8 @@ Build |package_name| environment variable. Use the ``--model_res`` argument to override the default or to explicitly select between these options. + The ``high_res`` (576x960) model requires more than 16GB of VRAM, so it only works on GPUs with more than 16GB of VRAM. + #. Build the package from source: .. code:: bash @@ -153,14 +157,14 @@ Run Launch File .. code:: bash ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=foundationstereo \ - engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_576x960.engine + engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_576x960.engine .. tab:: Low Resolution (low_res) .. code:: bash ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=foundationstereo \ - engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_320x736.engine \ + engine_file_path:=${ISAAC_ROS_WS:?}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_320x736.engine \ model_input_width:=736 model_input_height:=320 #. Open a **second terminal** and attach to the container: @@ -206,14 +210,14 @@ Run Launch File .. code:: bash ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=realsense_stereo_rect,foundationstereo \ - engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_576x960.engine + engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_576x960.engine .. tab:: Low Resolution (low_res) .. code:: bash ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=realsense_stereo_rect,foundationstereo \ - engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_320x736.engine \ + engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_320x736.engine \ model_input_width:=736 model_input_height:=320 .. tab:: ZED Camera @@ -235,7 +239,7 @@ Run Launch File .. code:: bash ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=zed_stereo_rect,foundationstereo \ - engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_576x960.engine \ + engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_576x960.engine \ interface_specs_file:=${ISAAC_ROS_WS}/isaac_ros_assets/isaac_ros_foundationstereo/zed2_quickstart_interface_specs.json .. tab:: Low Resolution (low_res) @@ -243,7 +247,7 @@ Run Launch File .. code:: bash ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=zed_stereo_rect,foundationstereo \ - engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_foundation_stereo_small_v1.0/foundationstereo_320x736.engine \ + engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/foundationstereo/deployable_v2.0/foundationstereo_320x736.engine \ interface_specs_file:=${ISAAC_ROS_WS}/isaac_ros_assets/isaac_ros_foundationstereo/zed2_quickstart_interface_specs.json \ model_input_width:=736 model_input_height:=320 diff --git a/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_depth_image_proc/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_depth_image_proc/index.rst.txt index d99d0cb46..be0046c22 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_depth_image_proc/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_depth_image_proc/index.rst.txt @@ -17,12 +17,29 @@ the ``depth_image_proc`` package. Available Components ^^^^^^^^^^^^^^^^^^^^ -======================== =========================================================================================================================================================================================================== ==================================================== =================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== -Component Topics Subscribed Topics Published Parameters -======================== =========================================================================================================================================================================================================== ==================================================== =================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== -``PointCloudXyzNode`` ``image_rect``, ``camera_info``: The depth image and the associated camera info with it ``points``: The resultant XYZ point cloud ``skip``: Skips ``skip`` number of depth pixels in order to limit the number of pixels converted to points. ``output_height`` The output height of the point cloud. This should be equivalent to the height of the image. ``output_width`` The output width of the point cloud. This should be equivalent to the width of the image. -``PointCloudXyzrgbNode`` ``depth_registered/image_rect``: The depth image ``rgb/image_rect_color``: The RGB image associated with the depth image ``rgb/camera_info``: The camera info associated with the RGB image and depth image ``points`` The resultant XYZRGB point cloud ``skip``: Skips ``skip`` number of depth pixels in order to limit the number of pixels converted to points. ``output_height`` The output height of the point cloud. This should be equivalent to the height of the image. ``output_width`` The output width of the point cloud. This should be equivalent to the width of the image. -======================== =========================================================================================================================================================================================================== ==================================================== =================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== +.. list-table:: + :header-rows: 1 + + * - Component + - Topics Subscribed + - Topics Published + - Parameters + * - ``PointCloudXyzNode`` + - ``image_rect``, ``camera_info``: The depth image and the associated camera info with it + - ``points``: The resultant XYZ point cloud + - ``skip``: Skips ``skip`` number of depth pixels in order to limit the number of pixels converted to points. ``output_height`` The output height of the point cloud. This should be equivalent to the height of the image. ``output_width`` The output width of the point cloud. This should be equivalent to the width of the image. + * - ``PointCloudXyzrgbNode`` + - ``depth_registered/image_rect``: The depth image ``rgb/image_rect_color``: The RGB image associated with the depth image ``rgb/camera_info``: The camera info associated with the RGB image and depth image + - ``points`` The resultant XYZRGB point cloud + - ``skip``: Skips ``skip`` number of depth pixels in order to limit the number of pixels converted to points. ``output_height`` The output height of the point cloud. This should be equivalent to the height of the image. ``output_width`` The output width of the point cloud. This should be equivalent to the width of the image. + * - ``AlignDepthToColorNode`` + - ``depth_image``, ``camera_info_depth``, ``camera_info_color``: The depth image, depth camera info, and color camera info. + - ``aligned_depth``: The aligned depth image. + - ``sync_queue_size``: The size of the queue for the synchronized subscribers. ``input_qos``: The input QoS for the subscribers. ``output_qos``: The output QoS for the publisher. ``use_cached_camera_info``: If true, using cached camera info and remove synchronization. ``enable_performance_logging``: If true, enable performance logging. + * - ``ConvertMetricNode`` + - ``image_raw``: The depth image in MONO16 format (millimeters). + - ``image``: The depth image in 32FC1 format (meters). + - ``input_qos``: The input QoS for the subscriber. ``output_qos``: The output QoS for the publisher. .. |package_name| replace:: ``isaac_ros_depth_image_proc`` \ No newline at end of file diff --git a/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_image_proc/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_image_proc/index.rst.txt index 8eba8d4df..a9192616c 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_image_proc/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_image_pipeline/isaac_ros_image_proc/index.rst.txt @@ -249,32 +249,38 @@ Visualize Results isaac-ros activate +#. Install ``rqt_image_view``: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-rqt-image-view + #. Observe the image_proc output on the terminal with the command: Resize: .. code:: bash - ros2 run image_view image_view --ros-args --remap image:=resize/image + ros2 run rqt_image_view rqt_image_view /resize/image Color Conversion: .. code:: bash - ros2 run image_view image_view --ros-args --remap image:=image_mono + ros2 run rqt_image_view rqt_image_view /image_mono Crop: .. code:: bash - ros2 run image_view image_view --ros-args --remap image:=crop/image + ros2 run rqt_image_view rqt_image_view /crop/image Rectify: .. code:: bash - ros2 run image_view image_view --ros-args --remap image:=image_rect + ros2 run rqt_image_view rqt_image_view /image_rect Flip: .. code:: bash - ros2 run image_view image_view --ros-args --remap image:=image_flipped + ros2 run rqt_image_view rqt_image_view /image_flipped Overview ^^^^^^^^ diff --git a/public/_sources/repositories_and_packages/isaac_ros_image_segmentation/isaac_ros_segment_anything2/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_image_segmentation/isaac_ros_segment_anything2/index.rst.txt index c6523e469..0fdb32695 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_image_segmentation/isaac_ros_segment_anything2/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_image_segmentation/isaac_ros_segment_anything2/index.rst.txt @@ -158,6 +158,17 @@ Prepare Segment Anything2 ONNX Model cp -r ${ISAAC_ROS_WS}/isaac_ros_assets/isaac_ros_segment_anything2/warmup ${ISAAC_ROS_WS}/isaac_ros_assets/models/segment_anything2/ +.. note:: + + Triton takes time to warm up the model. Wait until the model is loaded before adding objects to the segmentation model. + + The following sample log indicates that the model is loaded: + + .. code-block:: text + + [component_container_mt-1] I0214 13:32:46.556095 308280 model_lifecycle.cc:849] "successfully loaded 'segment_anything2'" + [component_container_mt-1] INFO: TrtISBackend id:217 initialized model: segment_anything2 + Run Launch File ~~~~~~~~~~~~~~~ diff --git a/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/index.rst.txt index 86214c271..91d94746c 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/index.rst.txt @@ -2,19 +2,15 @@ |package name| ========================== -.. note:: - - This package is only released as a Debian package and is not available in source form. +:ir_github:` ` Overview -------- -This package contains a thin ROS 2 wrapper for ISAAC Mapping package to expose the built libraries -and headers to ROS 2 ecosystem. - -It also contains tools for running the Isaac Mapping applications, including: +This package contains tools for rosbag conversion, stereo depth inference, and visual map creation, including: - ``rosbag_to_mapping_data``: a tool to convert rosbags to Isaac Mapping format, which is used for cuVGL map creation. - ``rosbag_poses_to_tum_format``: a tool to convert pose messages in the rosbag to `TUM `__ format, where each line contains a single pose of ``timestamp tx ty tz qx qy qz qw``. +- ``create_map_offline.py``: a script to create visual maps (cuVSLAM map, cuVGL map, occupancy map) from rosbag or raw images. Installation ------------ @@ -36,16 +32,10 @@ Launch dev container and install it with: sudo apt-get install -y ros-:ir_ros_distro:-isaac-mapping-ros - Tutorials --------- -.. toctree:: - :maxdepth: 1 - :glob: - - tutorial_map_creation.rst - +To create visual maps from a ROS bag, see :doc:`Tutorial: End-to-End Visual and Occupancy Map Creation `. Tools ----- diff --git a/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/tutorial_map_creation.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/tutorial_map_creation.rst.txt deleted file mode 100644 index 10b486d53..000000000 --- a/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_mapping_ros/tutorial_map_creation.rst.txt +++ /dev/null @@ -1,180 +0,0 @@ -Tutorial: End-to-End Visual and Occupancy Map Creation -====================================================== - -This tutorial describes how to create maps for visual localization including -visual global (cuVGL) localization map creation, cuVSLAM map creation, and -occupancy grid map creation. - -Map Types ---------- -The following list is a few different types of maps that are generated with -rosbags when running the :code:`create_map_offline.py` script. - -**cuVSLAM Map** - -cuVSLAM is able to create a map and load a saved map of an environment and use that map to -improve localization performance and maintain a consistent global frame of reference. - - -**Visual Global Localization Map** - -During startup or after losing localization, visual global localization can be -used to globally localize on a previously created map and operate in a shared -global frame. - -For more info about visual global localization, refer to: :doc:`Concepts: Visual Global Localization ` - -**Occupancy Grid Map** - -Navigation packages such as `nav2 `_ use an occupancy -grid map in order represent the obstacles in a map. `isaac_mapping_ros` uses :doc:`cuVSLAM ` -and :doc:`Nvblox ` to build an occupancy grid map from images. - -.. note:: - - - The generated occupancy map is only intended to be used for global path planning. Specifically it is not intended to be used for 2d Lidar localization. The generated map may contain slight artifacts and imprecisions and therefore is expected to be used with a planner that inflates obstacles. - - - Because the ROS2 rosbag replay is nondeterministic, each run of the occupancy map creation may produce a slightly different map. - -Data Collection ---------------- - -- Collect a rosbag using appropriate data recording tools. ``isaac_mapping_ros`` currently - supports H264 compressed images in the rosbag. -- Drive the robot around the environment and capture as much of the environment as - possible. We recommend moving the robot for at least 1 minute within a 5x5m area - where it can observe various objects like chairs, tables, shelves, and other office - furniture. Featureless environments or those with predominantly repetitive structures - can result in failed localization. - - For example, a blank wall with low feature is hard to localize against: - - .. figure:: - :ir_lfs:`` - :width: 800px - :alt: Driving towards a wall - :align: center - -- To generate a more accurate map, follow the guidelines for the robot's trajectories during data collection: - - - **Closed Loop Segments:** Build mapping trajectories in loops or segments of - around 5-10 meters. This ensures the same area is captured from different angles, which - improves map detail and reduces drift. - - - **Avoid Long Straight Paths:** Long drives in unexplored areas accumulate drift - risk. Use short, closed loops instead. - - - **Vary Camera Angles:** Capturing locations from multiple angles makes the visual - map more reliable for future localization. - - Schematic examples of efficient mapping paths in both narrow corridors and open - spaces, demonstrating optimal patterns for capturing comprehensive visual data - and reducing tracking drift. - - .. note:: - - For optimal pose correction and map accuracy, Loop Closing must - be effectively exploited. This mechanism corrects the robot's pose when - the robot revisits a previously mapped location. - - .. figure:: - :ir_lfs:`` - :width: 800px - :alt: Visualization of the mapping trajectory in corridor - :align: center - - .. figure:: - :ir_lfs:`` - :width: 800px - :alt: Visualization of the mapping trajectory in open space - :align: center - -- For localization rosbag collection, make sure to record at least 10s stationary - data at the beginning of the rosbag to allow the global localization to initialize correctly. - The localization trajectory should be in the mapping area and not deviate too much from - the mapping trajectory. - -Map Creation ------------- - -.. warning:: - - - Map Creation will use all the CPU and GPU resources, make sure you do not have anything important running at the same time. - - - Glass and very thin structures such as wires and cable railings cannot be detected by the current stereo networks used for depth estimation. If you have such structures in your environment, you might need to modify the environment so that there are larger visible features so that unnavigable areas are correctly estimated. - - - The quality of the occupancy map is dependent on the disparity data provided to nvblox. Degraded results may occur in wall corners. Improved results may be achieved with alternative stereo modalities, such as a different stereo camera or other AI/DNNs for stereo disparity estimation. - - -Make sure the rosbag and output map folder path are mounted to the Isaac ROS environment. You can -add them in ``~/.isaac_ros_dev-dockerargs`` then restart -the Isaac ROS environment. - -You can download the ``r2b_galileo`` dataset from the `r2b 2024 dataset on NGC `__ for this tutorial. -It is a 20-second bag containing synchronized images from four stereo camera pairs. - -Install `isaac_mapping_ros` and create the maps mentioned above using the following commands: - - .. run_ros_app_binary:: - :packages_up_to: isaac_mapping_ros - :package: isaac_mapping_ros - :asset_packages: isaac_ros_foundationstereo_models_install - :asset_scripts: install_foundationstereo_models.sh - :extra_packages: - :launch_args: - :app: create_map_offline.py --sensor_data_bag= --base_output_folder= - :command: run - - -Upon successful completion, verify that you see a message confirming that maps have -been created. The full logs for each step are stored in the outputs. All steps include: - -- `Extract edex` step extracts RGB images and metadata from rosbag. -- `Create cuVSLAM map` step computes the cuVSLAM pose and map. -- `Optimize odometry pose with keyframe pose` step processes the odometry pose and loop closures computed by cuVSLAM and outputs more accurate odometry poses. -- `Update frame metadata pose` step updates the image metadata with the computed poses. -- `Select map frames` step samples key frames using a translation and rotation distance from all images. -- `Copy map frames` step copies the sampled keyframes to a keyframe folder. -- `Run Foundation Stereo inference` step runs Foundation Stereo inference on keyframes and outputs depth images. -- `Run Nvblox` step creates a 2d occupancy map from keyframes using RGB+depth images and poses. -- `Extract features` step extracts ``ALIKED`` image features for keyframes. -- `Build vocabulary` step builds a visual vocabulary from extracted features. -- `Build BoW index` step builds a bag-of-words image retrieval database from extracted features, which together with vocabulary form the global localization map. - -The occupancy map for ``r2b_galileo`` dataset looks like this: - -.. figure:: - :ir_lfs:`` - :width: 800px - :alt: r2b_galileo_omap - :align: center - -A good occupancy map features well-aligned objects such as walls and overlapping -occupancy when the robot revisits the same locations. Misalignment in the map -is typically caused by pose errors. For example, this map with misaligned wall: - -.. figure:: - :ir_lfs:`` - :width: 800px - :alt: OMap poor quality - :align: center - -In this map, the wall marked is misplaced and should be more on the left: - -.. figure:: - :ir_lfs:`` - :width: 800px - :alt: OMap poor quality - :align: center - -To get a better map, try collecting a rosbag with more small loops in an -environment rich with visual features. A good map looks like this: - -.. figure:: - :ir_lfs:`` - :width: 800px - :alt: Good OMap - :align: center - -Ensure one map creation job runs at a time within a :code:`ROS_DOMAIN_ID`. You can run -simultaneous jobs within different :code:`ROS_DOMAIN_ID`. \ No newline at end of file diff --git a/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_ros_visual_global_localization/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_ros_visual_global_localization/index.rst.txt index 74d9b5bb7..5b5d16bf0 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_ros_visual_global_localization/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_mapping_and_localization/isaac_ros_visual_global_localization/index.rst.txt @@ -73,19 +73,19 @@ Install or Build |package name| source install/setup.bash + Tutorials ---------- -To create cuVGL map, see :doc:`Tutorial: cuVGL Map Creation `. +To create cuVGL map, refer to :doc:`Tutorial: cuVGL Map Creation `. -To localize with cuVGL, see :doc:`Tutorial: Localization with cuVGL `. +To localize with cuVGL, refer to :doc:`Tutorial: Localization with cuVGL `. Troubleshooting --------------- -For Isaac ROS setup issues, please check :doc:`here `. - +For Isaac ROS setup issues, refer to :doc:`troubleshooting `. API ---- @@ -112,14 +112,13 @@ ROS Parameter Type Default ``map_dir`` ``std::string`` ``""`` Required, the directory of cuVGL map files. ``config_dir`` ``std::string`` ``""`` Required, the directory of config files, which should include ``keypoint_creation_config.pb.txt`` and ``localizer_config.pb.txt``. ``model_dir`` ``std::string`` ``""`` The directory of model file. This value can be set in config file. -``input_image_topic_name`` ``std::string`` ``visual_localization/image`` The topic name of the input image. -``input_camera_info_topic_name`` ``std::string`` ``visual_localization/camera_info`` The topic name of the input camera info. +``input_image_topic_name`` ``std::string`` ``visual_localization/image`` The prefix of the input image topic name, the full topic name is ``_{i}`` for the :spelling:ignore:`i-th` camera. +``input_camera_info_topic_name`` ``std::string`` ``visual_localization/camera_info`` The prefix of the input camera info topic name, the full topic name is ``_{i}`` for the :spelling:ignore:`i-th` camera. ``localization_precision_level`` ``int`` ``2`` The localization precision level: 0 for lowest precision, returning more poses; 1 for medium precision; 2 for highest precision, returning fewer poses. *Frame Parameters* --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ``map_frame`` ``std::string`` ``vmap`` The frame name associated with the map origin. ``base_frame`` ``std::string`` ``base_link`` The frame name associated with the base of the robot or camera rig. -``camera_optical_frames`` ``std::vector`` ``[]`` The frame names associated with the cameras' optical frames. Using ROS optical frame conventions, i.e. z-axis front, y-axis down. If not specified will use the frames from the camera info messages. *Message Parameters* --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ``image_buffer_size`` ``int`` ``100`` Buffer size used by the image synchronizer. diff --git a/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_detectnet/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_detectnet/index.rst.txt index 84be7cbb0..9138e9b52 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_detectnet/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_detectnet/index.rst.txt @@ -195,6 +195,14 @@ Visualize Results isaac-ros activate +#. Install ``cv_bridge``: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-cv-bridge + +#. Run the visualizer: + .. code:: bash cd ${ISAAC_ROS_WS} && \ diff --git a/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_grounding_dino/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_grounding_dino/index.rst.txt index 8dd315674..60591841f 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_grounding_dino/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_grounding_dino/index.rst.txt @@ -196,6 +196,12 @@ Visualize Results isaac-ros activate +#. Install ``cv_bridge``: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-cv-bridge + #. Run the Grounding DINO visualization script: .. code:: bash diff --git a/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_rtdetr/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_rtdetr/index.rst.txt index f3127d7e9..76655c4fc 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_rtdetr/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_object_detection/isaac_ros_rtdetr/index.rst.txt @@ -216,6 +216,12 @@ Visualize Results isaac-ros activate +#. Install ``cv_bridge``: + + .. code:: bash + + sudo apt-get install -y ros-:ir_ros_distro:-cv-bridge + #. Run the RT-DETR visualization script: .. code:: bash diff --git a/public/_sources/repositories_and_packages/isaac_ros_pose_estimation/isaac_ros_dope/index.rst.txt b/public/_sources/repositories_and_packages/isaac_ros_pose_estimation/isaac_ros_dope/index.rst.txt index 542d07976..d37a41c46 100644 --- a/public/_sources/repositories_and_packages/isaac_ros_pose_estimation/isaac_ros_dope/index.rst.txt +++ b/public/_sources/repositories_and_packages/isaac_ros_pose_estimation/isaac_ros_dope/index.rst.txt @@ -124,7 +124,8 @@ Run Launch File .. code:: bash - pip3 install --break-system-packages torchvision + pip3 install --break-system-packages --no-deps --index-url https://download.pytorch.org/whl/cu130 torchvision==0.24.0+cu130 || \ + pip3 install --break-system-packages --no-deps --index-url https://download.pytorch.org/whl/cu130 torchvision==0.24.0 Now convert the model: diff --git a/public/_sources/troubleshooting/dev_env.rst.txt b/public/_sources/troubleshooting/dev_env.rst.txt index 0f402e5c5..09a408317 100644 --- a/public/_sources/troubleshooting/dev_env.rst.txt +++ b/public/_sources/troubleshooting/dev_env.rst.txt @@ -346,6 +346,101 @@ Solution NITROS nodes already have intraprocess communication enabled by default, with an exception of few publishers and subscribers that does not participate in data transfer. Disabling intraprocess communication by setting the parameter to ``False`` should resolve the issue and it does not hamper the performance. +.. _spark-rosdep-version-conflicts: + +``rosdep install`` fails on DGX Spark with package downgrade error +------------------------------------------------------------------ + +On DGX Spark platforms (bare-metal and virtual environment workflows only), +``rosdep install`` may fail because the system has newer versions of some packages than +those pinned by Isaac ROS. The Isaac ROS apt preference files in ``/etc/apt/preferences.d/`` +pin packages at priority 1001 to enforce tested versions. When ``apt`` needs to downgrade +any package to satisfy these pins, it rejects the **entire** transaction—meaning even +unrelated Isaac ROS packages fail to install. + +Symptom +~~~~~~~ + +.. code:: bash + + The following packages will be DOWNGRADED: + cuda-toolkit-13-config-common cuda-toolkit-config-common + E: Packages were downgraded and -y was used without --allow-downgrades. + +You may also see errors like the following when trying to launch Isaac ROS nodes, because +the packages were never installed: + +.. code:: bash + + Package 'nvblox_examples_bringup' not found: "package 'nvblox_examples_bringup' not found, searching: ['/opt/ros/jazzy']" + +Solution +~~~~~~~~ + +**Option 1: Allow downgrades** + +If this is a dedicated Isaac ROS system, you can configure ``apt`` to allow package +downgrades system-wide. This ensures the exact package versions tested with Isaac ROS +are installed, but **may break other software** on the system that depends on the newer +versions. + +.. code:: bash + + echo 'APT::Get::allow-downgrades "true";' | sudo tee /etc/apt/apt.conf.d/99allow-downgrades + +After setting this configuration, re-run the ``rosdep install`` command. You can remove +this configuration afterward: + +.. code:: bash + + sudo rm /etc/apt/apt.conf.d/99allow-downgrades + +**Option 2: Disable version pinning for conflicting packages** + +If you have other projects on the system that depend on the newer package versions, +you can disable the Isaac ROS apt preference files that cause the conflict. This allows +``apt`` to keep the DGX OS package versions instead of forcing a downgrade. These versions +are **not tested** with Isaac ROS and **may not work correctly**. + +The Isaac ROS apt preference files follow the ``isaac-ros-*.pref`` naming pattern in +``/etc/apt/preferences.d/``. Rename the relevant ones to disable them: + +.. code:: bash + + # For example, if CUDA packages are conflicting: + sudo mv /etc/apt/preferences.d/isaac-ros-cuda-13-0.pref /etc/apt/preferences.d/isaac-ros-cuda-13-0.pref.bak + +After renaming, re-run the ``rosdep install`` command. + +To restore the original pinning later: + +.. code:: bash + + sudo mv /etc/apt/preferences.d/isaac-ros-cuda-13-0.pref.bak /etc/apt/preferences.d/isaac-ros-cuda-13-0.pref + +H.264 Encode/Decode May Fail on DGX Spark +------------------------------------------ + +Symptom +~~~~~~~ + +On DGX Spark, the H.264 encoder and decoder nodes may fail to launch with the +following error: + +.. code:: bash + + Error: libnvbufsurface.so.1.0.0: cannot open shared object file: No such file or directory + +Solution +~~~~~~~~ + +This will be fixed in a future release. As a workaround, set the following +environment variable before launching the node: + +.. code:: bash + + export LD_LIBRARY_PATH="/usr/lib/aarch64-linux-gnu/nvidia:${LD_LIBRARY_PATH}" + Linker Error ``foo.so: file format not recognized; treating as linker script`` ------------------------------------------------------------------------------ diff --git a/public/about/contact.html b/public/about/contact.html index acc9a106f..f9cafaba2 100644 --- a/public/about/contact.html +++ b/public/about/contact.html @@ -61,7 +61,7 @@ - + @@ -390,8 +390,9 @@
  • Stereo DNN
  • Visual Global Localization
  • Visual SLAM
      @@ -506,10 +507,7 @@
  • Isaac ROS Mapping And Localization