Obstacle Detection and Map Building with a Rotating Ultrasonic Range Sensor using Bayesian Combination

Abstract

Map building and obstacle detection are basic tasks in mobile robot navigation. In this paper we present a probability based solution for map building which utilizes time of flight information from an ultrasonic sensor. In contrast to most of the available map building systems, this uses a single ultrasonic sensor, mounted on a rotating shaft. Discrete sonar observations taken at regular time intervals, by rotating the shaft in small step angles are incrementally merged into partial planes to produce a realistic representation of environment that is amenable to sonar localization. Readings of close proximity are averaged to suppress the transient errors and the results are further refined by using the sonar probability model to fill an occupancy grid and Bayesian combination for the purpose of data fusion. Experimental results obtained in a real indoor environment are presented to verify the validity of our algorithm.