Under severe weather or flow constrained areas, a new rerouting path planning model based on artificial potential field algorithm (APFA) was proposed.
在恶劣天气或流量受限条件下，建立了基于人工势场算法的改航路径规划模型。
The improvement artificial potential field law in the way plan was applied and simulated, and finally results indicated this algorithm considerably improved the robot avoiding collision.
在路径规划中应用了改进人工势场法并对其进行了仿真试验，结果表明其算法对于机器人的避碰有了可观的改善。
Firstly, the research of this paper is focus on preflight global planning algorithm based on cell decomposition methods and artificial potential field methods.
本文首先对基于栅格法和人工势场法思想的离线航迹规划算法进行了研究。
This Paper introduce extensive CMU algorithm combined with a potential field approach to control motion in robotic soccer.
本文提出了机器人足球赛中在卡耐基-梅隆大学（CMU）算法基础上，结合势场法进行多智能体行为控制的综合算法。
On the other hand, the path obtained by the artificial potential field method is optimized by the ant algorithm, which overcomes the local minima problem in the artificial potential field method.
另一方面，机器人的路径也同时得到优化，克服了人工势场法的局部极小问题。
The algorithm given in this paper inherits the basic idea of potential energy field method. By searching the minimum value of the energy function, the collision free path can be found.
算法继承了人工势场法的基本思想，通过寻找路径点的能量函数的极小值点而使路径避开障碍物。
The algorithm given in this paper inherits the basic idea of potential energy field method. By searching the minimum value of the energy function, the collision free path can be found.
算法继承了人工势场法的基本思想，通过寻找路径点的能量函数的极小值点而使路径避开障碍物。
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