Market-Based Robots Cooperative Exploration In Unknown Indoor Environment

Abstract

Multi-robot coordination is a useful and widely studied issue, particularly in the CSLAM application. For the exploration task in an unknown environment, it can reduce exploration time and enhance system efficiency. This paper mainly discusses the allocation algorithm for multiple robots. A good allocation algorithm can optimize the behavior of the robot team. This paper improves a market-based cooperative method, a new logic is added to prevent any robot from falling into idleness, and the assignments of every robot will be sorted by their new auction price each iteration. Two typical indoor environments are discussed over the algorithm efficiency, simulation of five kinds of contrastive algorithms to exploring the environment. Results show that the method proposed in this paper does the best for multi-robot exploration in the structural unknown environment.