Distributed optimization for the multi-robot system using a neurodynamic approach

Abstract

Abstract In this paper, we use a connected undirected graph to describe the multiple redundant manipulator system. An optimization model is formulated as a convex problem with coupled constraints. These constraints include equality constraints derived for path tracking, inequality constraints derived for obstacle avoidance, and convex sets built for joint physical limits. A novel distributed neurodynamics-based algorithm is developed for solving the complex problem in real time, so that there is no need for having a center coordinator in the multi-robot system. To verify the established model and the proposed algorithm, a dual-robot system is simulated to carry a rigid object following desired trajectories with obstacles considered. A more complex tri-robot system is simulated to perform as a supplementary evidence.