Wheel odometry is a method of estimating a mobile robot’s change in position and orientation by counting wheel rotations measured with encoders and applying a kinematic motion model. As an instance of dead reckoning, it integrates incremental wheel displacement over time to track pose relative to a starting point. It is simple and low-cost but accumulates drift from wheel slip, uneven terrain and calibration error, so it is typically fused with other sensors.
- Wheel odometry estimates a Mobile Robot’s pose change from Encoder readings of wheel rotation combined with a Kinematics motion model, a form of Dead Reckoning.
- It feeds Localisation and Navigation but accumulates drift over distance.
Overview
- By measuring how far each wheel turns, the robot computes incremental translation and rotation, integrating these to track its position relative to a start point.
- The approach is cheap and self-contained, requiring no external infrastructure, but small per-step errors compound, especially under wheel slip or uneven terrain.
- In practice it is fused with inertial and exteroceptive sensors to bound drift, contrasting with vision-based Visual Odometry.
Key aspects
- Encoder-based measurement of wheel rotation.
- Kinematic model converting wheel motion to body pose change.
- Incremental integration producing relative pose estimates.
- Drift accumulation from slip, terrain and calibration error.
- Sensitivity to accurate wheel-radius and track-width calibration.
Mechanisms
- Encoder ticks are converted to wheel displacement, combined through the drive kinematics into linear and angular velocity, and integrated to update the estimated pose.
Applications
- Low-level motion tracking for Mobile Robot platforms.
- Prediction step in SLAM and Sensor Fusion estimators.
- Short-horizon Pose Estimation between absolute fixes.
- Differential-drive and wheeled-robot navigation.