No version for distro humble showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro jazzy showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro kilted showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro lyrical showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro rolling showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro galactic showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro iron showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro melodic showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

CONTRIBUTING

No version for distro noetic showing github. Known supported distros are highlighted in the buttons above.

ros2go2estimator repository

fusion_estimator

ROS Distro
github

Repository Summary

Description
Checkout URI	https://github.com/shineminxing/ros2go2estimator.git
VCS Type	git
VCS Version	main
Last Updated	2026-08-13
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Packages

Name	Version
fusion_estimator	0.0.0

README

CAPO-LeggedRobotOdometry 🦾

Chinese version readme.md is in contributting.md.

CAPO-LeggedRobotOdometry is a pure proprioceptive odometry library for legged robots, implemented with a portable C++ estimator core that depends only on IMU and joint motor data.

The core estimation logic is implemented in FusionEstimator/fusion_estimator.h. The file fusion_estimator_node.cpp provides a ROS 2 wrapper around this estimator, while the Matlab/ folder contains examples for MATLAB + C++ mixed compilation and offline evaluation.

For side-by-side comparison, Matlab/Comparison/invariant-ekf/ provides a MATLAB mixed-compilation workflow for invariant-ekf, making it easier to compare this repository against a representative open-source legged odometry baseline.

In 3D closed-loop trials (a 200 m horizontal and 15 m vertical loop), Astrall point-foot robot A achieves 0.1638 m horizontal error and 0.219 m vertical error; for wheel-legged robot B, the corresponding errors are 0.2264 m and 0.199 m.

Welcome to add my wechat 401435318 and join a wechat group.

📄 Paper

Contact-Anchored Proprioceptive Odometry for Quadruped Robots (arXiv:2602.17393)

Paper: https://arxiv.org/abs/2602.17393

If you use this repository in research, please consider citing the paper.

To help readers quickly validate the pipeline, we provide Go2-EDU trial datasets, including real-world videos, derived CSV files, and the corresponding ROS bag topics/messages required by this node, enabling fast reproduction and sanity checks.

Download (GitHub Releases): https://github.com/ShineMinxing/CAPO-LeggedRobotOdometry/releases/tag/DataForTest
Recommended assets in that release include GO2Flat, GO2Stairs, MPXY150Z10, MWXY150Z10, robot_flat_1_compress.zip, and robot_stairs_1_compress.zip

Note: the IMU on this Go2-EDU platform exhibits noticeable yaw drift, so the odometry accuracy is generally worse than the results reported for Astrall robots A and B in the paper.

✨ Key Features

Category	Description
Biped / Quadruped / Wheel-Legged Unified	Online contact-set switching; stance legs are detected automatically, supporting fast transitions between standing and walking.
IMU + Joint-Motor Only	The estimator core works with only IMU and joint motor measurements, without requiring cameras or LiDAR.
MATLAB / C++ Mixed Compilation	The `Matlab/` folder provides MATLAB + MEX examples for calling the same C++ core, and `Matlab/Comparison/invariant-ekf/` includes a comparable mixed-compilation setup for `invariant-ekf`.
Full 3D & Planar 2D	Publishes both 6DoF odometry (`SMX/Odom`) and a gravity-flattened 2D odometry (`SMX/Odom_2D`).
Portable Pure C++ Core	The estimator core is isolated in `FusionEstimator/`, making it easier to reuse outside ROS2.
Runtime Tuning	Key parameters can be adjusted through `config.yaml`, and platform-dependent thresholds can be tuned for different robots.

Scope	Repository	Summary
Low-level / Drivers	https://github.com/ShineMinxing/Ros2Go2Base	DDS bridge, Unitree SDK2 control, pointcloud→LaserScan, TF utilities
Odometry	CAPO-LeggedRobotOdometry (this repo)	Pure proprioceptive fusion, publishes `SMX/Odom` / `SMX/Odom_2D`
SLAM / Mapping	https://github.com/ShineMinxing/Ros2SLAM	Integrations for Cartographer 3D, KISS-ICP, FAST-LIO2, Point-LIO
Voice / LLM	https://github.com/ShineMinxing/Ros2Chat	Offline ASR + OpenAI Chat + TTS
Vision	https://github.com/ShineMinxing/Ros2ImageProcess	Camera pipelines, spot / face / drone detection
Gimbal Tracking	https://github.com/ShineMinxing/Ros2AmovG1	Amov G1 gimbal control and tracking
Tools	https://github.com/ShineMinxing/Ros2Tools	Bluetooth IMU, joystick mapping, gimbal loop, data logging

⚠️ Clone as needed. If you only need state estimation, this repository is sufficient. For mapping, it is natural to pair it with Ros2SLAM and Ros2Go2Base.

📂 Repository Layout

CAPO-LeggedRobotOdometry/
├── CMakeLists.txt
├── package.xml
├── config.yaml
├── fusion_estimator_node.cpp        # ROS2 wrapper around the C++ estimator core
├── FusionEstimator/                 # portable pure C++ estimator core
│   ├── Estimators/
│   ├── fusion_estimator.h           # main estimator entry
│   ├── LowlevelState.h
│   ├── SensorBase.cpp
│   ├── SensorBase.h
│   ├── Sensor_IMU.cpp
│   ├── Sensor_IMU.h
│   ├── Sensor_Legs.cpp
│   ├── Sensor_Legs.h
│   └── Readme.md
├── Matlab/                          # MATLAB + MEX examples for the same C++ core
│   ├── build_mex.m
│   ├── fusion_estimator.m
│   ├── fusion_estimator_mex.cpp
│   ├── Comparison/
│   │   └── invariant-ekf/           # MATLAB mixed-compilation workflow for invariant-ekf
│   └── ...                          # optional test datasets are published via GitHub Releases
├── Plotjuggler.xml
└── Readme.md

🧩 Architecture Notes

File truncated at 100 lines see the full file

ros2go2estimator repository

ROS Distrogithub

Repository Summary

Packages

README

CAPO-LeggedRobotOdometry 🦾

📄 Paper

📦 Data Sharing (Go2-EDU ROS bags)

✨ Key Features

🏗️ Related Repositories

📂 Repository Layout

🧩 Architecture Notes

CONTRIBUTING

ros2go2estimator repository

ROS Distrogithub

Repository Summary

Packages

README

CAPO-LeggedRobotOdometry 🦾

📄 Paper

📦 Data Sharing (Go2-EDU ROS bags)

✨ Key Features

🏗️ Related Repositories

📂 Repository Layout

🧩 Architecture Notes

CONTRIBUTING

ros2go2estimator repository

ROS Distrogithub

Repository Summary

Packages

README

CAPO-LeggedRobotOdometry 🦾

📄 Paper

📦 Data Sharing (Go2-EDU ROS bags)

✨ Key Features

🏗️ Related Repositories

📂 Repository Layout

🧩 Architecture Notes

CONTRIBUTING

ros2go2estimator repository

ROS Distrogithub

Repository Summary

Packages

README

CAPO-LeggedRobotOdometry 🦾

📄 Paper

📦 Data Sharing (Go2-EDU ROS bags)

✨ Key Features

🏗️ Related Repositories

📂 Repository Layout

🧩 Architecture Notes

CONTRIBUTING

ros2go2estimator repository

ROS Distrogithub

Repository Summary

Packages

README

CAPO-LeggedRobotOdometry 🦾

📄 Paper

📦 Data Sharing (Go2-EDU ROS bags)

✨ Key Features

🏗️ Related Repositories

📂 Repository Layout

🧩 Architecture Notes

CONTRIBUTING

ros2go2estimator repository

ROS Distrogithub

Repository Summary

Packages

README

CAPO-LeggedRobotOdometry 🦾

📄 Paper

📦 Data Sharing (Go2-EDU ROS bags)

✨ Key Features

🏗️ Related Repositories

📂 Repository Layout

🧩 Architecture Notes

CONTRIBUTING

ros2go2estimator repository

ROS Distrogithub

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github

ROS Distro
github