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A time-optimization algorithm for soccer robot's path-planning in dynamic environment

机译:动态环境下足球机器人路径规划的时间优化算法

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In order to optimize the robot's motion time, smooth Bezier curves instead of broken line were used to describe the motion path of the robot due to its satisfaction of nonholonomic constraint equation and the ability to control the direction of robot at the target point. A genetic algorithm (GA) was studied to optimize the control points of Bezier curve. The effects (security, length and smoothness of the path) on the motion time were considered in the fitness function of GA. Under the dynamic environment, the potential collision was constructed by predicting the possible position of the obstacles and the avoiding-collision robot in every time slice, and the reliability of prediction related to the distance between obstacle and the robot was considered in evaluation of the security factor of the fitness function. The results from the simulation demonstrate the efficiency of the proposed method.
机译:为了优化机器人的运动时间,由于其满足非完整约束方程式以及在目标点控制机器人方向的能力,因此使用光滑的Bezier曲线代替了虚线来描述机器人的运动路径。研究了遗传算法(GA)以优化Bezier曲线的控制点。在GA的适应度函数中考虑了运动时间的影响(路径的安全性,长度和平滑度)。在动态环境下,通过预测障碍物和避碰机器人在每个时间片中的可能位置来构造潜在的碰撞,并在安全性评估中考虑与障碍物和机器人之间的距离有关的预测的可靠性适应度函数的因子。仿真结果表明了该方法的有效性。

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