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Research on Trajectory Planning of Manipulator Based on GA - APF Algorithm

机译:基于GA-APF算法的机械臂轨迹规划研究。

摘要

A novel approach of trajectory optimization in the field of trajectory planning of a six-DOF manipulator is presented. In this paper, the kinematic model of the manipulator is easily established by using classical D-H parameter method, and the kinematics results of the manipulator are validated with MATLAB. Then Monte Carlo method is used to obtain the workspace of manipulator. This optimization method of trajectory planning, whose principle is that applying genetic algorithm (GA) to a modified artificial potential field (APF) method, is to address the optimal path searching problem in field of obstacle avoidance trajectory planning of manipulator. A set of optimized parameters are obtained by genetic algorithm, and are used to conduct a simulation, which shows a better trajectory compared with other method. Finally, the experiment is conducted by using UR10 robot. Both the simulation and experimental results show the validity and the effectiveness of GA-APF algorithm.
机译:提出了一种六自由度机械手轨迹规划领域中轨迹优化的新方法。本文采用经典的D-H参数法,可以很容易地建立机械臂的运动学模型,并用MATLAB验证机械臂的运动学结果。然后使用蒙特卡洛方法获得机械手的工作空间。这种轨迹规划的优化方法,其原理是将遗传算法(GA)应用于改进的人工势场(APF)方法,旨在解决机械手避障轨迹规划领域中的最优路径搜索问题。通过遗传算法获得了一组优化的参数,并进行了仿真,与其他方法相比具有更好的轨迹。最后,使用UR10机器人进行了实验。仿真和实验结果均表明了GA-APF算法的有效性和有效性。

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