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rf2o_laser_odometry package from ugv_ws repo

apriltag apriltag_msgs apriltag_ros cartographer costmap_converter costmap_converter_msgs emcl2 explore_lite openslam_gmapping slam_gmapping ldlidar rf2o_laser_odometry robot_pose_publisher teb_local_planner teb_msgs vizanti vizanti_cpp vizanti_demos vizanti_msgs vizanti_server ugv_base_node ugv_bringup ugv_chat_ai ugv_description ugv_gazebo ugv_interface ugv_nav ugv_slam ugv_tools ugv_vision ugv_web_app

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Package Summary

Tags	No category tags.
Version	0.1.0
License	GPL v3
Build type	AMENT_CMAKE
Use	RECOMMENDED

Repository Summary

Description
Checkout URI	https://github.com/waveshareteam/ugv_ws.git
VCS Type	git
VCS Version	ros2-humble-develop
Last Updated	2025-02-25
Dev Status	UNKNOWN
Released	UNRELEASED
Tags	No category tags.
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Package Description

Estimation of 2D odometry based on planar laser scans. Useful for mobile robots with innacurate base odometry. For full description of the algorithm, please refer to: Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach. ICRA 2016 Available at: http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/papers/217

Additional Links

No additional links.

Maintainers

Javier G. Monroy

Authors

Mariano Jaimez
Javier G. Monroy

src/ugv_else/rf2o_laser_odometry/README.md

rf2o_laser_odometry

Estimation of 2D odometry based on planar laser scans. rf2o is a fast and precise method to estimate the planar motion of a lidar from consecutive range scans. Useful for mobile robots with inaccurate wheel odometry.

For every scanned point we formulate the range flow constraint equation in terms of the sensor velocity, and minimize a robust function of the resulting geometric constraints to obtain the motion estimate. Conversely to traditional approaches, this method does not search for correspondences but performs dense scan alignment based on the scan gradients, in the fashion of dense 3D visual odometry.

The very low computational cost (0.9 milliseconds on a single CPU core) together whit its high precision, makes RF2O a suitable method for those robotic applications that require planar odometry.

For a full description of the algorithm, please refer to: Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach. ICRA 2016 Available at: http://mapir.uma.es/papersrepo/2016/2016_Jaimez_ICRA_RF2O.pdf

CHANGELOG

No CHANGELOG found.

Package Dependencies

Deps	Name
	geometry_msgs
	rclcpp
	std_msgs
	tf2
	tf2_ros
	cmake_modules
	sensor_msgs
	tf2_geometry_msgs
	ament_cmake
	eigen3_cmake_module

System Dependencies

Name
eigen

Dependant Packages

Name	Deps
robolaunch_cloudy_navigation

Launch files

No launch files found

Messages

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Services

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Plugins

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API Docs Browse Code

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