Market-based algorithms and fuzzy methods for the navigation of mobile robots

An important aspect of the navigation of mobile robots is the avoidance of static and dynamic obstacles. This paper deals with obstacle avoidance using artificial potential fields and selected traffic rules. The potential field method is optimized by a mixture of fuzzy methods and market-based optimization (MBO) between competing potential fields of mobile robots. Here, depending on the local situation, some potential fields are strengthened and some are weakened. The optimization takes place especially when several mobile robots act in a small area. In addition, to avoid an undesired behavior of the mobile platform in the vicinity of obstacles, central symmetrical potential fields are `deformed´ by using fuzzy rules.