Multi-Robot Navigation Using Market-Based Optimization

Abstract

This paper deals with artificial force potential fields for obstacle avoidance and their optimization by a market-based approach in scenarios where several robots are acting in a shared area. Specifically, the potential field method is enhanced by fuzzy logic, traffic rules, and market-based optimization (MBO). Fuzzy rules are used to deform repulsive potential fields in the vicinity of obstacles to produce smoother motions around them. Traffic rules are used to deal with situations where robots are crossing each other. MBO, on the other hand, is used to strengthen or weaken repulsive potential fields generated due to the presence of other robots. For testing and verification, the navigation strategy is implemented and tested in simulation of more realistic vehicles. Issues while implementing this method and limitations of this navigation strategy are also discussed. Extensive simulation experiments are performed to examine the improvement of the traditional potential field (PF) method by the MBO strategy.