Planning the trajectory of an autonomous wheel loader and tracking its trajectory via adaptive model predictive control

Abstract

In a typical operation mode, a wheel loader frequently accelerates and decelerates, and the curvature of the driving path is inconsistent. In the past, autonomous vehicle trajectory planning has not considered the related changes in the velocity of the vehicle. Therefore, the trajectory tracking control process has seldom considered the impact of curving paths on the trajectory tracking performance. To address these problems, this study evaluated an autonomous wheel loader based on the trajectory of its non-uniform driving motion and constructed an adaptive model predictive control (AMPC) trajectory tracking system that considers disturbances in the path curvature. The trajectory of the autonomous wheel loader was then tracked using the proposed AMPC system with a planned non-uniform motion trajectory as the target. Its performance was then compared with that of a conventional model predictive control (MPC) trajectory tracking system that does not consider any path curvature disturbances. The maximum displacement error and heading error obtained by the proposed AMPC system were found to be 65.7% and 60%, respectively, smaller than those obtained by the MPC system. The desired trajectory can also be tracked well under different curvature amplitudes using the AMPC trajectory tracking system, ensuring active safety performance of an autonomous wheel loader in the process of trajectory tracking.