Obstacle Detection and Feature Extraction using 2.5D Range Sensor System

This paper describes a new sensor system for improving the accuracy of the range information using multiple IR range sensors. In most of the mobile robot application, the robot enters an unknown environment and relying solely on range sensor information, it builds up an environment map that can be used for collision free navigation and localization. Mobile robot builds the environment map for localization and navigation from the range sensor information. Therefore, the accuracy of the map depends on the accuracy of the range sensor information, so do the localization and navigation. A sensor system with multiple rotating range sensors is proposed in this paper. There are 12 IR range sensors around the mobile robot. Each sensor rotates and the scanning area of a sensor overlaps with those of the nearby sensors. The advantage of the proposed idea is that the blind spot becomes much smaller than using only one sensor. In order to scan the environment vertically, a 2.5D sensor system is developed. It is more effective than the 3D vision system in some sense that it provides the stereoscopic range information without any computational image processing. The scanned data can be used for the enhanced map building and map matching