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‎.gitignore‎

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.bundle
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vendor/bundle
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Gemfile.lock
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.vscode/

‎LICENSE‎

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‎README.md‎

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## License
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The content of this repository and the generated website is open-sourced under the Apache-2.0 license. See the [LICENSE](LICENSE) file for details. Please note the following third-party elements and content:
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The content of this repository and the generated website is open-sourced under the Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) license.
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You are free to:
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* **Share** — copy and redistribute the material in any medium or format for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms.
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Under the following terms:
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* **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
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* **NoDerivatives** — If you remix, transform, or build upon the material, you may not distribute the modified material.
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* **No additional restrictions** — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
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See the [LICENSE](LICENSE) file for details.
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Please note the following third-party elements and content:
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* The website is based on the MIT-licensed template [Jekyll Doc Theme](https://github.com/aksakalli/jekyll-doc-theme) by [Can Güney Aksakalli](https://github.com/aksakalli/) and contributors. The template files and source code can be identified by the commits by his user name [aksakalli](https://github.com/aksakalli/) and by the user names of the contributors in the git history. Starting point for the development of this website was the version as of 23 September 2018, cf. commit [3cc3f49](https://github.com/micro-ROS/micro-ROS.github.io/commit/3cc3f492b80db80d87a310cbdc3895425a09db5e).
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‎_data/authors.yml‎

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amx-piap:
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name: Alexandre Malki
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github: amx-piap
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francesca-finocchiaro:
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name: Francesca Finocchiaro
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github: FranFin
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link: github

‎_data/docs.yml‎

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- title: Overview
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docs:
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- overview
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- overview/features
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- overview/hardware
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- overview/transports
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- overview/comparison
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- overview/ROS_2_feature_comparison
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- overview/docker_ci_status
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- overview/users_and_clients
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- concepts/client_library
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- concepts/client_library/real-time_executor
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- concepts/client_library/system_modes
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- concepts/client_library/embedded_tf
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- concepts/client_library/decision_paper
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- concepts/client_library/rcutils_analysis
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- concepts/benchmarking/concept
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- concepts/benchmarking/results
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- title: Memory profiling
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docs:
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- concepts/memo_prof
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- title: Core Tutorials
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- tutorials/core/overview

‎_docs/concepts/client_library/embedded_tf/index.md‎

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---
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Table of contents
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- [Introduction and Goal](#introduction-and-goal)
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- [Requirements](#requirements)
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- [Design](#design)
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- [Implementation of tf2_filter](#implementation-of-tf2_filter)
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- [Roadmap](#roadmap)
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- [Acknowledgments](#acknowledgments)
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## Introduction and Goal
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The TF transform graph, with its support for both a temporal history, and distributed information sources, has been a novel tool for robotics frameworks when it was released in 2008. Functionally, it is based in scene graph concepts known from computer graphics [[Foote 2013]](https://ieeexplore.ieee.org/document/6556373), but these only rarely offer distribution, and did not offer temporal histories at all (mainly, because this is not needed for frame-based rendering applications like in computer graphics). Distributed scene graphs have become more widely available also in computer graphics. In robotics, work by de Laet et al. [[De Laet et al. 2013]](https://ieeexplore.ieee.org/document/6696693) has extended transforms graphs to also contain twist (i.e., angular motion) information, and to provide more compile-time error checking. This is currently not integrated with distribution mechanisms, but could be used on a single system.
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One persistent issue with transform graphs has been their resource use. ROS TF works through replicated copies of the entire transform tree at every node that uses it, and is implemented through unicast TCP connections between nodes. In systems with many dynamic parts, this has sometimes been called the ``TF firehose``, because of the large stream of incoming messages.
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micro-ROS will go beyond this state of the art by running the dynamic transform tree in an embedded device, while keeping resource use to a minimum based on an analysis of the spatial and temporal details actually necessary. Further, enabling real-time queries even in the face of concurrent updates through integration will be realized through integration with the micro-ROS real-time executor. It is also planned to integrate the embedded TF will with the node lifecycle to achieve further power-savings
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## Requirements
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Embedded TF requirements are documented at: [github.com/micro-ROS/geometry2/blob/ros2/tf2_filter/docs/requirements.md](https://github.com/micro-ROS/geometry2/blob/ros2/tf2_filter/docs/requirements.md).
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## Design
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The Embedded TF design is documented at: [github.com/micro-ROS/geometry2/blob/ros2/tf2_filter/docs/design.md](https://github.com/micro-ROS/geometry2/blob/ros2/tf2_filter/docs/design.md).
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## Implementation of tf2_filter
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Implementation of tf2_filter for ROS 2 and micro-ROS can be found at: [github.com/micro-ROS/geometry2/blob/ros2/tf2_filter/](https://github.com/micro-ROS/geometry2/blob/ros2/tf2_filter/).
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## Roadmap
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**2018**
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* Static filter approach in the agent allowing to specify the parts of the kinematic chain that are relevant for an application component on micro-ROS.
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**2019**
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* Design and implement an embedded TF implementation which is integrated with the real-time executor in a way that removes the need for costly synchronization primitives.
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**2020**
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* Design and implement an API extension, as well as a reference implementation for custom transform representations that increase run-time efficiency.
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This task has been cancelled as discussed in the EU project review in September 2019.
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## Acknowledgments

‎_docs/concepts/client_library/index.md‎

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* [Real-Time Executor](real-time_executor/)
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* [System Modes](system_modes/)
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* [Embedded Transform (TF)](embedded_tf/)

‎_docs/concepts/memo_prof/3mems.png‎

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