Path Tracking Control of Car-like Wheeled Mobile Robot on the Slope based on Nonlinear Model Predictive Control

To expand the application scenarios of autonomous robot, a path tracking control method for a car-like wheeled mobile robot (CWMR) on the slope is proposed in this study. Firstly, a CWMR dynamic model considering gravity disturbance and internal load transfer is established to reduce the accumulation of modeling errors during the state prediction process. And then the kinematics expression of the robot's full pose is established by using the transformation relationship of spatial coordinates, thereby the terrain geometry parameters can be used as the control input for feedback correction of model-based prediction. Afterwards, fully considering the unstructured terrain constraints, a CWMR active steering controller is designed based on nonlinear model predictive control (NMPC) to realize the minimum tracking error. Finally, a simulation platform was built to verify the effectiveness of the proposed method in medium and high speed conditions.

Automated summary

A path tracking control method for a car-like wheeled mobile robot (CWMR) on the slope is proposed in this study. The method establishes a dynamic model and kinematics expression for the CWMR, and designs an active steering controller based on nonlinear model predictive control to achieve minimum tracking error.