零空间优化的有效覆盖三维表面使用冗余操纵

Jürgen Hess, Gian Diego Tipaldi, Wolfram Burgard
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引用次数: 46

摘要

研究了三维曲面上冗余机械手覆盖路径规划中的零空间最小化问题。现有的覆盖解决方案只关注欧几里得代价函数,并且通常返回相对于联合空间的次优路径。在这里描述的方法中,我们通过将不同的逆运动学解作为图中的单个节点来明确地考虑零空间,并将问题建模为广义旅行推销员问题(GTSP)。GTSP是TSP的推广,其中图的节点被细分为簇,并且每个簇中至少需要访问一个节点。我们使用PR2机器人和复杂物体来评估我们的方法。我们的结果表明,我们的方法在操作工作量和完成时间方面优于欧几里得覆盖算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Null space optimization for effective coverage of 3D surfaces using redundant manipulators
In this paper we consider the problem of null space minimization in coverage path planning of 3D surfaces for redundant manipulators. Existing coverage solutions only focus on Euclidean cost functions and often return suboptimal paths with respect to the joint space. In the approach described here, we explicitly consider the null space by treating different inverse kinematics solutions as individual nodes in a graph and model the problem as a generalized traveling salesman problem (GTSP). The GTSP is a generalization of the TSP where the nodes of the graph are subdivided into clusters and at least one node in each cluster needs to be visited. We evaluate our approach using a PR2 robot and complex objects. Our results demonstrate that our method outperforms Euclidean coverage algorithms in terms of manipulation effort and completion time.
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