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Trajectory planning of a redundant planar manipulator based on joint classification and particle swarm optimization algorithm

机译:基于联合分类和粒子群优化算法的冗余平面操纵器的轨迹规划

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This paper presents a general method for the trajectory planning of the redundant planar manipulator. The mathematical relation between joint space and Cartesian space in a two-dimensional space is first derived. The joint classification is employed to obtain the solutions of corresponding joints. It divides joints into class I redundant joints, class II redundant joints, and nonredundant joints. The new application of knot points in the quintic B-spline curve is introduced to generate inverse solutions of class I redundant joints. Examples show that the number and distribution of knot points have a large effect on their solutions. Moreover, the particle swarm optimization algorithm is extended to generate solutions of class II redundant joints. It also optimizes the initial trajectories of joints and end-effector. Finally, solutions of nonredundant joints can be generated by the derived relation between the joint space and Cartesian space. The proposed methodology is confirmed by a case study. Under the same conditions, results show that the solution obtained by the extended method is not only better than that obtained by the particle swarm optimization algorithm but also closer to the global optimal solution.
机译:本文介绍了冗余平面操纵器的轨迹规划的一般方法。首先导出了二维空间中的联合空间和笛卡尔空间之间的数学关系。采用联合分类来获得相应关节的溶液。它将关节分为I级冗余关节,II类冗余关节和非冗余关节。引入了Quintic B样条曲线中的结点的新应用,以产生I类冗余关节的逆溶液。例如,结点的数量和分布对其解决方案有很大影响。此外,粒子群优化算法扩展到生成II类冗余关节的解决方案。它还优化了关节和末端效应器的初始轨迹。最后,可以通过联合空间和笛卡尔空间之间的衍生关系来产生非还原联接的解决方案。通过案例研究证实了所提出的方法。在相同的条件下,结果表明,通过扩展方法获得的解决方案不仅优于通过粒子群优化算法获得的解决方案,而且还更接近全局最优解。

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