Slip-Based Autonomous ZUPT through Gaussian Process to Improve Planetary Rover Localization

Abstract

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.

8 pages, 6 figures, 2 tables

References in corpus (3)

• Gaussian process regression for forecasting battery state of health
• Perception-aware Autonomous Mast Motion Planning for Planetary Exploration Rovers
• Improved Planetary Rover Inertial Navigation and Wheel Odometry Performance through Periodic Use of Zero-Type Constraints

Cited by in corpus (4)

• ZUPT Aided GNSS Factor Graph with Inertial Navigation Integration for Wheeled Robots
• Evaluation of the Benefits of Zero Velocity Update in Decentralized EKF-Based Cooperative Localization Algorithms for GNSS-Denied Multi-Robot Systems
• Proprioceptive Slip Detection for Planetary Rovers in Perceptually Degraded Extraterrestrial Environments
• A Comparison of Robust Kalman Filters for Improving Wheel-Inertial Odometry in Planetary Rovers