Motion Coordination for Distributed Agents in Cellular Warehouse Problem and Its Evaluation

Abstract

An approach to coordinate motions of transport tables for cellular warehouse problem is shown. In the proposed approach, the tables are considered to be autonomous agents, and a built-in behavior function given by ANNs and the evolved problem-oriented connection weights navigate the agents to their specified goals. To determine the agent to be moved, a measure of the priority to move is introduced, and the measure of each agent changes according to the results of its own motions and local interactions among neighboring agents. The solution of the problem is a motion sequence of agents. Through various numerical experiments, we show the applicability of the proposed method and examine the contribution of the evaluation criteria to the learning result of behavior function.