Fuzzy based traversability analysis for a mobile robot on rough terrain

Yusuke Tanaka, Yonghoon Ji, Atsushi Yamashita, Hajime Asama

Abstract: We present a novel rough terrain traversability analysis method for mobile robot navigation. We focused on the scenario of mobile robot operation in a disaster environment with limited sensor data. The robot builds a map in real time and analyzes the terrain traversability of its surrounding environment. The proposed method is based on fuzzy inference so that it can handle uncertainties in the sensor data. Two values associated with the terrain traversability, roughness and slope, are calculated from an elevation map built by a laser range finder mounted on the mobile robot. These two values are inputted to the fuzzy inference, and the traversability is analyzed. Based on the traversability output from the fuzzy inference, a vector field histogram (VFH) is generated. The mobile robot course is determined according to the VFH. We demonstrated our algorithm on an artificial environment. The experimental results showed that the mobile robot was able to reach the target position safely while avoiding untraversable areas.