1.Nantong University;2.Nanjing University of Aeronautics and Astronautics
The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)
The local minimum problem caused by path planning of potential field has received much more attention. To cope with this issue, in this paper, the relationship between the potential force field and the velocity direction was analyzed when the robot has been trapped in the local minimum, and an obstacle avoidance method based on the motion cumulative angle was proposed. The internal and external turning angles of robot were taken to appraise the relationship between the direction and angle of the robot. Based on the angle cumulative, the "key reset point" was defined. By refreshing its own position and resetting its cumulative angle, the complex environment was simplified and the path planning was realized in an unknown environment. Simulation studies indicated that proper switching conditions for each state were designed to guarantee the orders of the state switching and smooth operation, and therefore the robot can improve the flexibility and reliability of decision. Compared to some existing methods, the method has the advantages for shorter paln path and higher efficiency. The feasibility of this method was verified in path planning experiment by the self-made mobile robot. These results showed that the proposed algorithm was suitable for the first time through the unknown complex environment and the scenario of path planning without mapping.