Safe Corridor-Based MPC for Follow-Ahead and Obstacle Avoidance of Mobile Robot in Cluttered Environments

Abstract

In cluttered environments, a human-following mobile robot must predict the motion intention of the followed human and take environmental obstacles into consideration. Consequently, it brings several challenges, such as the human’s detour direction prediction problem and the visibility maintenance problem for route planning. To overcome these problems, this paper proposes an integrated follow-ahead framework, in which the human’s detour behavior is predicted by the Leg Motion Model-based EKF (LMM-EKF) and the iterative human route search algorithm, followed by the Safe Corridor-based Model Predictive Controller (SCMPC) used to obtain the optimal control solution. Also, a new perspective about visibility is provided in this paper that, via placing multiple obstacle-free safe regions along the human’s intended direction without any complex preprocessing for the point cloud, SCMPC prevents the robot from collision and occlusion simultaneously based on the basic properties of the convex set. The validity of the proposed method is comprehensively verified through real-world experiments.