This paper describes a new method for improving the azimuth accuracy of range information using conventional (Polaroid) low-resolution ultrasonic sensors mounted in a circular array on a mobile robot. Although ultrasonic sensors are fairly accurate in measuring distance in depth, they commonly have significant uncertainty in azimuth. We model this uncertainty with a uniform distribution along an arc. This means that the echo has an equal likelihood of originating from any point along the arc. We then introduce a new method to fuse sonar data to better approximate the actual obstacle location. This new method is termed the arc transversal median method because the robot determines the location of an object 1) by intersecting one arc with other arcs, 2) then by considering only "transversal" intersections, those which exceed a threshold in angle, and 3) by taking the median of the intersections. The median is a robust estimator that is insensitive to noise; a few stray readings will not affect its value. We show, via some simple geometric relationships, that this method can improve the azimuth accuracy of the sonar sensor by a specified amount under well-defined conditions. Experimental results on an ultrasonic sensor array situated on a mobile robot verify this approach.

This paper describes a new method for determining range information about a robot's surroundings using low resolution ultrasonic sensors. These sensors emit ultrasound which bounces off of nearby objects and returns to the sensor. The time-of-flight for the sound to return to the sensor is the distance between the sensor and the object. A sonar arc represents the possible locations of the object. We model these locations with a simple uniform probability distribution on the sonar arc. We then introduce a new method to fuse sonar data to determine the actual obstacle location. This new method is termed the arc-transversal median method because the robot determines the location of an object by intersecting one arc with other arcs whose angle-of-intersection exceeds a threshold and then taking the median of the intersection. The median is a robust estimator that is insensitive to noise because a few stray readings will not affect the median. We show via some simple geometric relationships, that this method can improve the accuracy of the sonar sensor by a specified amount, when certain assumptions were in place. Finally, experimental results on a real mobile robot verify this approach.