Traction Control of Wheeled Robotic Vehicles in Rough Terrain with Application to Planetary Rovers

Abstract

Mobile robots are being developed for high-risk missions in rough terrain situations, such as planetary exploration. Here, a rough-terrain control methodology is presented that exploits the actuator redundancy found in multiwheeled mobile robot systems to improve ground traction and reduce power consumption. The algorithm optimizes individual wheel torque based on multiple optimization criteria, which are a function of the local terrain profile. A key element of the method is to be able to include estimates of wheel-terrain contact angles and soil characteristics. A method using an extended Kalman filter is presented for estimating these angles using simple on-board sensors. Simulation and experimental results for a micro-rover traversing challenging terrain demonstrate the effectiveness of the algorithm.