Abstract
This paper presents a novel approach to high-resolution ultrasonic environment imaging for autonomous mobile systems. It describes the fusion of sensor data from multiple wide-angled ultrasonic transducers with overlapping detection cones for creating local environment models. A fitting technique defined as tangential regression is introduced that considers sensor properties as well as physical reflection properties of ultrasound. This allows a reliable detection and localization of straight-line segments which describe the boundary of geometric objects. Experimental results show that straight-line segments extracted at different robot locations can be aggregated and merged in order to obtain a global environment map
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