A Robust Lateral Control Architecture for Off-Road Vehicle Guidance on Deformable Soils

To address the challenges of off-road mobile robotics, we have developed an innovative lateral control solution for vehicles with a front steering axle. This approach ensures stability and minimizes lateral error during trajectory tracking while being robust to variations in tire-ground interaction and vehicle speed. The theoretical study, along with experimental results obtained using our off-road experimental vehicle KIPP, are presented in this journal article.

This paper introduces a novel lateral guidance strategy for autonomous ground vehicles operating in deformable environments. The strategy combines a geometric algorithm with a dynamic controller to leverage the advantages of both methods. The geometric algorithm is based on a modified Pure Pursuit method, which calculates the lateral error by considering a dynamic parameter associated with the look-ahead distance. The controller takes model uncertainties and time-variant parameters into account in a grid-based LPV (Linear Parameter Varying) synthesis. To validate the proposed control architecture, a dedicated off-road vehicle simulator that accounted for deformable soils was used. The effectiveness and robustness of the proposed lateral guidance strategy were demonstrated by integrating and validating the control architecture on a vehicle prototype. The results indicate that the proposed approach effectively handled complex and uncertain deformable environments. Overall, this study presents a new lateral guidance strategy that enhances the performance and reliability of autonomous ground vehicles in challenging environments.