Point Stabilization of Nonholonomic Mobile Robot by Bézier Smooth Subline Constraint Nonlinear Model Predictive Control

Abstract

Mobile robotic machining is a feasible mode of manufacturing large-scaled and complex-shaped workpieces, where point stabilization is executed by the mobile robot for arriving at the machining station. Localization accuracy, avoidance of environment obstacle, and reliability of the motion path are the key points that should be concerned during the robotic machining scene. However, the fixed-point control usually leads to discontinuous motion for nonholonomic mobile robots; thereby, oscillation and jerks easily occurring in the unsmooth movement. To cope with this phenomenon, a novel Bézier smooth subline constraint nonlinear model predictive control is presented, where point control problem is addressed in high quality by converting it into a dynamic tracking control problem. Specifically, the smoothness of the moving trajectory is constrained by Bézier smooth subline and optimized through the minimum variation curves principle. Then, an error-based dynamic model predictive tracking controller is designed to guarantee the motion accuracy. As a result, the nonholonomic mobile robot can reach the desired position reliably by following the elaborately designed trajectory. Compared with traditional point stabilization approaches, in this article, our method is featured by subline constraint; thereby, exhibiting smooth and excellent moving states with the collision-free property. Furthermore, high positioning accuracy can be guaranteed through precise dynamic control. The feasibility and superiority of the proposed method are demonstrated through contrast simulations and real experiments.