Division of Iterative-Transportation Based on State Estimation Using Local Observation

Abstract

This paper deals with a framework of decentralized approach to division of labor by multiple mobile robots. An iterative-transportation task by multiple robots with multiple sets of starts (pick-up place of the object) and goals (put down place) is considered as the task. On each route between a start and a goal, the efficiency of transportation improves when the number of robots increases. Due to jams, however, excessive number of robots on the same route causes inefficiency. We propose a control law of each robot to choose an appropriate route so as to optimize the total efficiency of the transportation, where each robot utilizes information which can be obtained only by local observation (without any explicit communication among robots). The proposed control is based on the estimation of the number of robots on the routes in the future by using EXPAR model. In simulation, it was verified that the proposed control law realized the similar level of the efficiency by appropriately choosing the route, compared with the case where global information can be utilized.