Model Predictive Optimization and Terminal Sliding Mode Motion Control for Mobile Robot With Obstacle Avoidance

Abstract

This article proposes an optimization dynamic movement primitives (ODMP) strategy and terminal sliding mode motion control (TSMC) method for the generalization problem of mobile robot when facing with obstacles. In scenarios where obstacles are present along the reproduced trajectories, an online trajectory planning algorithm based on model predictive optimization ensures that the robot reproduces the demonstrated trajectory as closely as possible without colliding with obstacles, in which the obstacles are modeled as the soft and hard constraint simultaneously, and the model predictive control (MPC) is utilized to search optimal solutions for path planning in the presence of obstacle. Additionally, a dynamic controller based on super-twisting practice terminal sliding mode (ST-PTSM) control ensures rapid and accurate tracking of the trajectories planned by MPC while improve accuracy during tracking, thus ensuring convergence within a finite convergence time. Experiments on a two-wheeled differential mobile robot are carried out to verify the proposed method.