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Research on path planning of real-time obstacle avoidance of mechanical arm based on genetic algorithm

机译:基于遗传算法的机械臂实时避障路径规划研究

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Aiming at the problem that modular mechanical arm may collide with the obstacles in working space at runtime, a path planning algorithm of obstacle avoidance is proposed based on a genetic algorithm (GA). Firstly, the Denavita??Hartenberg method is applied to the modelling of the mechanical arm; then, the kinematic and kinetic analysis is conducted and the kinematic and kinetic equations of the mechanical arm are established. On this basis, the time, spatial distance and path length of the motion are regarded as optimising indices and the optimisation of path planning of obstacle avoidance is achieved using GA for mechanical arm under a working condition with single obstacle or multiple obstacles. Through simulation, the effectiveness and feasibility of a path planning algorithm of mechanical arm obstacle avoidance based on GA is verified. This algorithm improves the efficiency of a mechanical arm to avoid the obstacles in working space at runtime.
机译:针对模块化机械臂在运行时可能与工作空间中的障碍物碰撞的问题,提出了一种基于遗传算法的避障路径规划算法。首先,将Denavita ?? Hartenberg方法应用于机械臂的建模。然后进行了运动学和动力学分析,建立了机械臂的运动学和动力学方程。在此基础上,将运动的时间,空间距离和路径长度作为优化指标,并在单个或多个障碍物的工作条件下,采用遗传算法对机械臂进行避障路径规划的优化。通过仿真,验证了基于遗传算法的机械臂避障路径规划算法的有效性和可行性。该算法提高了机械臂的效率,从而避免了运行时工作空间中的障碍。

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