Fuzzy maps: A new tool for mobile robot perception and planning

Abstract

An essential component of an autonomous mobile robot is the exteroceptive sensory system. Sensing capabilities should be integrated with a method for extracting a representation of the environment from uncertain sensor data and with an appropriate planning algorithm. In this article, fuzzy logic concepts are used to introduce a tool useful for robot perception as well as for planning collision-free motions. In particular, a map of the environment is defined as the fuzzy set of unsafe points, whose membership function quantifies the possibility for each point to belong to an obstacle. The computation of this set is based on a specific sensor model and makes use of intermediate sets generated from range measures and aggregated by means of fuzzy set operators. This general approach is applied to a robot with ultrasonic rangefinders. The resulting map building algorithm performs well, as confirmed by a comparison with stochastic methods. The planning problem on fuzzy maps can be solved by defining various path cost functions, corresponding to different strategies, and by searching the map for optimal paths. To this end, proper instances of the A* algorithm are devised. Experimental results for a Nomad 200™ robot moving in a real-world environment are presented. © 1997 John Wiley & Sons, Inc.