Quadrant based incremental planning for mobile robots
来源期刊：中南大学学报(英文版)2014年第5期
论文作者：P. Raja M. Abhilash K. Ravi Shankar Alameluvari Adarsh
文章页码：1792 - 1803
Key words：mobile robots; incremental planning; quadrant based approach; dynamic environment
Abstract: Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem. A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable (on-line) environment is proposed. The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated. Also, the governing equations for the shortest path are derived. The proposed mathematical model describes the motion (satisfying constraints of the mobile robot) along a collision-free path. Further, the algorithm is applicable to dynamic environments with fixed or moving targets. Simulation results show the effectiveness of the proposed algorithm. Comparison of results with the improved artificial potential field (iAPF) algorithm shows that the proposed algorithm yields shorter path length with less computation time.
P. Raja, M. Abhilash, K. Ravi Shankar, Alameluvari Adarsh
(School of Mechanical Engineering, SASTRA University, Thanjavur 613401, Tamilnadu, India)
Abstract:Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem. A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable (on-line) environment is proposed. The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated. Also, the governing equations for the shortest path are derived. The proposed mathematical model describes the motion (satisfying constraints of the mobile robot) along a collision-free path. Further, the algorithm is applicable to dynamic environments with fixed or moving targets. Simulation results show the effectiveness of the proposed algorithm. Comparison of results with the improved artificial potential field (iAPF) algorithm shows that the proposed algorithm yields shorter path length with less computation time.
Key words:mobile robots; incremental planning; quadrant based approach; dynamic environment
