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An Improved APF Method for Complex and Dynamic Obstacles' Avoidance
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AI
DOI：10.1142/S2301385023410054.png)
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Abstract
En 中文
In this paper, an improved artificial potential field (APF) method combined with Bug2 is proposed for dynamic obstacle avoidance of mobile robots, which eliminates the trajectory oscillations and avoids failure when encountering a complex obstacle. First, the problems of avoidance failure and trajectory oscillations of the relative position and velocity-based APF were analyzed. Then, a Bug2-based APF method is proposed by using the M-line of Bug2 to optimize the avoidance trajectory. The proposed method makes the angle of the virtual repulsion force tangent to the obstacle, which results in avoidance that the trajectory surrounds the obstacle along with the M-line. Finally, the effectiveness and practicability of the proposed method are demonstrated by performing many simulations and experiments. The results show that the proposed method can realize safe and autonomous dynamic obstacle avoidance and significantly improve the robot's success rate and obstacle avoidance efficiency.
Keywords:
Omnidirectional mobile robot
artificial potential field
Bug2 algorithm
dynamic obstacle avoidance