Terrain Mapping and Control Optimization for a 6-Wheel Rover with Passive Suspension

Rough terrain control optimization for space rovers has become a popular and challenging research field. Improvements can be achieved concerning power consumption, reducing the risk of wheels digging in and increasing ability of overcoming obstacles. In this paper, we propose a terrain profiling and wheel speed adjustment approach based on terrain shape estimation. This terrain estimation is performed using sensor data limited to IMU, motor encoders and suspension bogie angles. Markov Localization was also implemented in order to accurately keep track of the rover position. Tests were conducted inand outdoors in low and high friction environments. Our control approach showed promising results in high friction environment: the profiled terrain was reconstructed well and, due to wheel speed control, wheel slippage could be also decreased. In the low friction sandy test bed however, terrain profiling still worked reasonably well, but uncertainties like wheel slip were too large for a significant control performance improvement.