Abstract
In this paper, we propose a method for travelable area detection using a 3DLIDAR. In order for the autonomous mobile robot to travel safely, travelable area detection is necessary in such areas where traveling becomes hard by differences in the height and material changes. Our system is integration of evaluations suitable for each such factors that make traveling hard. The evaluations are composed of the height information, the curvature estimation, the classification of the reflection intensity. Afterwards, we construct a local environment map of the robot from detected results. The effectiveness of the proposed method is proved through the experiments results in outdoor environments.
