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- Title
Path planning of lunar robot based ondynamic adaptive ant colony algorithmand obstacle avoidance.
- Authors
Shinan Zhu; Weiyi Zhu; Xueqin Zhang; Tao Cao
- Abstract
Path planning of lunar robots is the guarantee that lunar robots can complete tasks safely and accurately. Aiming at theshortest path and the least energy consumption, an adaptive potential field ant colony algorithm suitable for path planningof lunar robot is proposed to solve the problems of slow convergence speed and easy to fall into local optimum of antcolony algorithm. This algorithm combines the artificial potential field method with ant colony algorithm, introduces theinducement heuristic factor, and adjusts the state transition rule of the ant colony algorithm dynamically, so that thealgorithm has higher global search ability and faster convergence speed. After getting the planned path, a dynamic obstacleavoidance strategy is designed according to the predictable and unpredictable obstacles. Especially a geometric methodbased on moving route is used to detect the unpredictable obstacles and realize the avoidance of dynamic obstacles. Theexperimental results show that the improved adaptive potential field ant colony algorithm has higher global search abilityand faster convergence speed. The designed obstacle avoidance strategy can effectively judge whether there will becollision and take obstacle avoidance measures.
- Subjects
ROBOTIC path planning; ANT algorithms; ROBOTS; OBSTACLE avoidance (Robotics); ALGORITHMS; HUMAN-machine relationship
- Publication
International Journal of Advanced Robotic Systems, 2020, Vol 17, Issue 3, p1
- ISSN
1729-8806
- Publication type
Article
- DOI
10.1177/1729881419898979