Spatial-Based Model Predictive Path Following Control for Skid Steering Mobile Robots

Abstract

This paper presents a model predictive path following control (MPPFC) framework for driving skid-steered mobile robots (SSMRs) in the presence of obstacles. A spatial kinematic model is used to develop a model along a predefined path while avoiding any incidental stationary obstacles. Extensive computation experiments executed on a physical robot simulator environment demonstrate that the proposed control approach effectively ensures robot convergence to a reference path with minimal deviations. The employed MPPFC parameters are presented for easy repeatability of the presented computation experiments and further utilization of the proposed control framework.