An Improved Potential Field Method for Robot Path Planning
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摘要: 在应用传统人工势场法的移动机器人路径规划问题中,机器人对移动障碍物避障效率较低,路径中存在局部极小点。针对这些缺陷,构建了一种基于势流理论的势场模型。在该模型中,势流理论中的概念与路径规划中的概念一一对应,修正函数解决了势流理论中与路径规划问题的矛盾之处,如点汇处速度无穷大等。为了保证对移动障碍物避障的可靠性,应用茹科夫斯基变换对势场分布及函数进行了改进。模型经改进后,为解决局部极小问题,本文进一步使用了点涡的概念,此后又加入虚拟点源以优化轨迹。最后,讨论了多障碍物势场加权叠加方法。仿真实验中,在多种避障情景下对比了改进前后的势场法。仿真结果表明,改进势场能够引导机器人对移动障碍物进行灵活避障,在避免局部极小点时较传统方法更为有效。Abstract: For mobile robot path planning based on traditional artificial potential field, the avoidance to movable obstacle is inefficient and there are local minima in the generated path. To solve this problem, an improved potential field model based on potential flow theory is proposed. In the improved model, the corresponding relationship between potential flow theory and path planning is introduced. Conflicts, for instance that velocity is infinite in the position of sink, are resolved by modified function. To satisfy the reliability of avoiding mobile obstacle, Zhukovsky transformation is used to optimize the configuration and function of potential model. A further investigation of vortex is applied to prevent the local minima. After that, the concept of virtual source is introduced for path planner to generate an optimized trajectory. In the end, the issue of multi-obstacle potential superposition is discussed. To verify the algorithm, comparisons between improved method and traditional one by various circumstances in simulation are conducted. The simulation results indicate that in the improved method, potential field is able to lead robot to avoid mobile obstacles according to velocity vectors of obstacles. Besides, the method is more efficient when preventing local minima.
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