An Adaptive Whole-Body Control Approach for Dynamic Obstacle Avoidance of Mobile Manipulators for Human-Centric Smart Manufacturing

Abstract

In human-centric smart manufacturing (HCSM), the robot's dynamic obstacle avoidance function is crucial to ensuring human safety. Unlike the static obstacle avoidance of manipulators or mobile robots, the dynamic obstacle avoidance in mobile manipulators presents challenges such as high-dimensional planning and motion deadlock. In this paper, an adaptive whole-body control approach for dynamic obstacle avoidance of the mobile manipulators for HCSM is proposed. Firstly, an adaptive global path planning method is proposed to reduce planning dimension. Secondly, lateral coupling effect term and nonlinear velocity damping constraints are formulated to alleviate motion deadlock. Then, a whole-body dynamic obstacle avoidance motion controller is presented. Through simulations and real-world experiments, the planning time is reduced by 18.65% on average, and the path length by 15.94%, compared to the global RRT benchmark algorithm. The dynamic obstacle avoidance experiment simulates the obstacle combinations such as pedestrians moving in opposite direction, traversing and forming a circle during the robot operation. The proposed motion controller can adjust robot movement in real time according to the change of its relative distance from obstacles, meanwhile maintaining an average safe distance of 0.45 m from dynamic obstacles. It is assumed that the proposed approach can benefit dynamic human–robot symbiotic manufacturing tasks from more natural and efficient manipulations.