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An Improved Artificial Potential Field Method Based on Chaos Theory for UAV Route Planning

机译:基于混沌理论的无人机航路规划改进人工势场方法

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This paper proposes a modified artificial potential field method based on chaos theory. In this algorithm, the search algorithm of chaos theory is introduced into the potential field function of artificial potential field method, which changes the repulsion coefficients of obstacles and the gravitational coefficients of target points. This method resolves the defects of the traditional artificial potential field method, such as the local optimum problem, the inability to find the path between the close obstacles, the oscillation in front of the obstacles, and the oscillation in the narrow channel. Simulation experiments show that this algorithm can not only effectively solve the problems of the unmanned aerial vehicle (UAV) in the route planning, such as easily falling into the minimum and wandering around the end point, but also realize the route planning in complex situations, reduce the flight cost, and improve the speed and accuracy of the UAV route planning.
机译:提出了一种基于混沌理论的改进人工势场方法。该算法将混沌理论的搜索算法引入到人工势场法的势场函数中,改变了障碍物的排斥系数和目标点的重力系数。该方法解决了传统的人工势场方法的缺陷,例如局部最优问题,无法找到附近障碍物之间的路径,障碍物前面的振动以及狭窄通道中的振动。仿真实验表明,该算法不仅可以有效解决无人机在航路规划中的问题,如容易掉到最小并在终点附近徘徊,还可以实现复杂情况下的航路规划。降低飞行成本,提高无人机航路规划的速度和准确性。

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