Configuration-aware Model Predictive Motion Planning in Narrow Environment for Autonomous Tractor-trailer Mobile Robot

Abstract

A novel collision-free motion planner was proposed for tractor-trailer mobile robots (TTMRs) in a narrow environment with consideration of the polygonal shape of the TTMR and obstacles. The motion planner was designed as an iterative nonlinear optimization problem with a receding horizon similar to the model predictive control. Collision-free constraints with a configuration of the TTMRs were derived from the Farkas’ lemma with simplification, which were the hard constraints in the optimization problem. As such, the proposed method guarantees collision avoidance in its motion planning. The presented modified Farkas’ lemma stabled the fluctuated calculation time during the optimization. Numerical simulations confirmed the validity of the proposed method. A thorough evaluation of the dynamic environment with a moving obstacle was also carried out.