The approach of extracting features from the local environment for mobile robot

Abstract

A new data fusion method to extract features from the local environment for a mobile robot's navigation has been developed and implemented. This method, named the obstacle group, compresses data in a series of levels in order to reduce the quantity of data for communication between modules in a distributed single-robot system, or between all the robots and the central station in a multi-robot system. The method based on a grid map and an active window has strong adaptability and is real-time in a crowded environment. Experimental results demonstrate that the robot can successfully avoid collisions and plan its path by using this method.