Added first draft of embedded TF subpage.

Signed-off-by: Ralph Lange <ralph.lange@de.bosch.com>

Author: ralph-lange

embedded_tf/index.md

@@ -0,0 +1,42 @@
+# Embedded TF
+
+Table of contents
+
+*   [Introduction and Goal](#introduction-and-goal)
+*   [Requirements](#requirements)
+*   [Design](#design)
+*   [Implementation of tf2_filter](#Implementation-of-tf2_filter)
+*   [Roadmap](#roadmap)
+*   [Acknowledgments](#acknowledgments)
+
+
+## Introduction and Goal
+
+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 framebased 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 not currently integrated with distribution mechanisms, but could be used on a single system.
+
+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 microROS real-time executor. It is also planned to integrate the embedded TF will with the node lifecycle to achieve further power-savings
+
+
+## Requirements
+
+... are documented at [github.com/microROS/geometry2/blob/ros2/tf2_filter/docs/requirements.md](https://github.com/microROS/geometry2/blob/ros2/tf2_filter/docs/requirements.md).
+
+
+## Design
+
+... is documented at  [github.com/microROS/geometry2/blob/ros2/tf2_filter/docs/design.md](https://github.com/microROS/geometry2/blob/ros2/tf2_filter/docs/design.md).
+
+
+## Implementation of tf2_filter
+
+... can be found at  [github.com/microROS/geometry2/blob/ros2/tf2_filter/](https://github.com/microROS/geometry2/blob/ros2/tf2_filter/).
+
+
+## Roadmap
+
+...
+
+
+## Acknowledgments
+
+This activity has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 780785).

index.md

@@ -17,7 +17,8 @@ We'll update this README as we proceed. For now, you can check out our work on:
  - Real-Time Operating System: [https://github.com/microROS/NuttX](https://github.com/microROS/NuttX)
  - Micro-ROS in RTOS example applications: [apps](https://github.com/microROS/apps)
  - Predictable scheduling and execution:  [real-time_executor](real-time_executor/)
- - System modes and system hierarchy: [system-modes](system_modes/)
+ - System modes and system hierarchy: [system_modes](system_modes/)
+ - Embedded transform (tf) library: [embedded_tf](embedded_tf/)
  - Reference hardware: [https://github.com/microROS/hardware](https://github.com/microROS/hardware)
  - Build infrastructure for embedded development using docker: [https://github.com/microROS/docker](https://github.com/microROS/docker)