wheel-odometry-model

What problem does it solve?

Configures and calibrates wheel odometry models for differential-drive robots, enabling accurate pose estimation by converting encoder ticks to linear and angular motion and managing covariance settings.

Core Features & Use Cases

• Kinematics modeling: compute v and omega from wheel data for differential drive.
• Encoder-to-distance mapping: convert encoder ticks to linear distance using wheel diameter and ticks-per-rev.
• Pose integration & covariance management: update pose and configure covariance for localization.
• ROS integration examples: demonstrates a Python node skeleton and robot_localization integration guidance.

Quick Start

Configure wheel_diameter, wheel_separation, and ticks_per_rev, and run the odometry node to publish odometry.