Slip-Based Autonomous ZUPT through Gaussian Process to Improve Planetary Rover Localization
This work addresses localization challenges for planetary rovers in rough terrain, representing an incremental improvement by optimizing existing methods without hardware changes.
The paper tackles the problem of balancing localization accuracy and traversal rate for planetary rovers by autonomously initiating stops for zero-velocity updates based on predicted wheel slippage, achieving over 97% 3D localization accuracy over 650 m drives on rough terrain.
The zero-velocity update (ZUPT) algorithm provides valuable state information to maintain the inertial navigation system (INS) reliability when stationary conditions are satisfied. Employing ZUPT along with leveraging non-holonomic constraints can greatly benefit wheeled mobile robot dead-reckoning localization accuracy. However, determining how often they should be employed requires consideration to balance localization accuracy and traversal rate for planetary rovers. To address this, we investigate when to autonomously initiate stops to improve wheel-inertial odometry (WIO) localization performance with ZUPT. To do this, we propose a 3D dead-reckoning approach that predicts wheel slippage while the rover is in motion and forecasts the appropriate time to stop without changing any rover hardware or major rover operations. We validate with field tests that our approach is viable on different terrain types and achieves a 3D localization accuracy of more than 97% over 650 m drives on rough terrain.