Fast and Robust Frontier Line Segment Extracting Method Based on FCM for Robot Exploration

Accessible frontier is an important factor for mobile robot autonomous exploration. This paper presents a fast and robust frontier line segment extracting method based on fuzzy c-means clustering algorithm for robot exploration. Firstly, the proposed method divides robot's local occupancy map into sub-regions with same size. In the next step, this paper analyzes the characteristic of robot exploration frontier with occupancy grid map, and the optimal number of FCM cluster center in each sub-region is defined. Consequently, line segments corresponding to exploration frontiers based on fuzzy c-mean algorithm are calculated in sub-region level to alleviate the extensive computation. Following those steps, line segments merging, line endpoints extending and line excluding are conducted to get more accurate frontier segment parameters in global level. In the end, the effectiveness of proposed method is verified by experiments results in lab environment.