Robust motion planning methodology for autonomous tracked vehicles in rough environment using online slip estimation

Abstract

This paper presents a robust motion planning methodology for autonomous tracked vehicles navigating in a rough and unknown environment. Two fields of study are dealt with in this paper: motion planning and slip estimation. For the motion planner, the CC-RRT* algorithm is combined with LQG-MP. The motion planner uses a chance-constrained approach and considers the role of compensator in the planning step to provide a robust yet non-conservative planner. For the slip estimator, a stable yet practical online approach known as IPEM is used. IPEM compares the integrated prediction with the measurement to calculate appropriate parameters. The methodology performs online slip estimation and re-planning iteratively. This guarantees the safe travel of the vehicle even when there is an unexpected terrain change that can be fatal. The simulation result shows that the iterative estimation and re-planning plays a significant role in ensuring the safety of the vehicle.