An Improved Potential Field Path Planning Algorithm for Multiple Robots
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摘要: 针对多机器人在实际作业中面临的全局拥堵问题和对人类避障问题提出了三种改进势场。为保证机器人之间的基础避碰,使用社群势场定义机器人之间的相互作用力。当人类与机器人在环境中共存时,使用行为势场,兼顾机器人移动效率和对人类避障,以寻求安全与效率之间的平衡。提出防堵势场以识别并避免全局拥堵。在仿真中,结合三种势场,对提出的规划方法的有效性进行了验证。通过投影的实验结果将改进前后的方法进行了对比,进一步说明了提出方法较传统方法效率更高。Abstract: In this paper, three types of potential field are proposed to solve global congestion and human obstacle avoidance in the practical operation of multiple robots. The social potential field determines the interaction force among the robots and ensures their avoidance foundation. The behavior potential field aims to strike a balance between human safety and the movement productivity of the robots when there are both robots and human in the working environment. The anti-congestion potential field is to distinguish and prevent global congestion. The simulation results verify the validity of the proposed method by using the resultant potential of three kinds of potential field. Moreover, the experimental results on a real robot are presented and further indicate that the improved algorithm is more efficient than the traditional ones.
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Key words:
- multiple robots /
- path planning /
- artificial potential field /
- behavior potential field
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