Escaping from obstacle zone for mobile robot based on maximum distance priority mechanism

This paper presents an obstacle avoidance method of escaping from obstacle zone based on maximum distance priority mechanism, aiming at the obstacle avoidance with limited local environmental information instead of known global environmental information. Acquiring local environmental information by laser range finder (LRF) which collects distance data between object and mobile robot, we use a method of finding feasible directions to search feasible sections, which are divisions of LRF distance data. And a maximum distance priority mechanism is proposed to select feasible section containing maximum distance as reference motion section, enabling mobile robot always to move in the direction of escaping from obstacle zones. Meanwhile, error control is designed to optimize the method and make it more practical. An analysis experiment of laser range finder data from three representative scenes is carried out to demonstrate the principle of the proposed method. Besides, we conduct a contrast experiment in MT-R wheeled mobile robot between maximum distance priority mechanism and maximum open angle priority mechanism. In the end, maximum distance priority mechanism overcomes the problems for mobile robot, which includes endless wandering and turning around in obstacle zone. The results of experiments illustrate effectiveness of the proposed method, and reveal its well real-time performance and obstacle avoidance efficiency.