一种求解机器人关节运动轨迹的有效方法

Hang Dong, M. Cong, Dong Liu, Guifei Wang
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引用次数: 9

摘要

最小震动(MJ)轨迹引入较少的机器人振动,并希望其平滑运动,而最小距离(MD)轨迹要求限制机器人操纵器的预期和意外路径。MJ轨迹和MD轨迹的结合为机器人应用提供了一种有效的运动学方案。提出了一种基于时间间隔优化的方法,在不考虑机械臂动力学和避障的情况下,利用三次样条曲线在关节空间内求解机器人的全局最小抖动和最小距离轨迹。三次样条用于保证关节位移、速度和加速度连续性的框架中。首先,考虑样条曲线的边界条件和MJ和MD约束,构造了一个极大极小优化问题。然后,采用基于时间间隔分析的遗传算法进行求解。在此基础上,给出了运动方案的全局解。最后,将我们的结果与另一种MJ规划器的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An effective technique to find a robot joint trajectory of minimum global jerk and distance
Minimum-jerk (MJ) trajectories introduce less robot vibrations and are desirable for their smooth movement, while Minimum-distance (MD) trajectories are required to limit both the expected and unexpected paths of robot manipulators. The combination of the MJ and MD trajectories provides an effective kinematic scheme for robotic applications. An approach based on time spacing optimization is developed to find the global minimum-jerk as well as minimum-distance trajectory of a robot manipulator within joint space using cubic splines, despite the fact that the manipulator dynamics as well as the obstacle avoidance are not taken into account. Cubic splines are used in a framework which guarantees the continuity of joint displacements, velocities and accelerations. Firstly, a minimax optimization problem is formulated by respecting the boundary conditions of the splines and the MJ and MD constraints. Then, the problem is solved by genetic algorithms based on time spacing analysis. After that, a global solution of the kinematic scheme is provided. Finally, a comparison is made between our results and that of an alternative MJ planner.
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