Combining arm and hand metrics for sensible grasp selection
Combining arm and hand metrics for sensible grasp selection
复制标题
结合手臂和手的指标进行合理的抓握选择
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
H. Christensen
中科院分区：
文献类型：
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作者：
A. H. Quispe;H. B. Amor;H. Christensen
在本文中，我们提出了一种方法，机器人把握优先级的基础上结合手臂和手的度量。大多数传统的方法基于以手为中心的指标来评估抓握，例如力闭合、手指伸展、接触表面积和类似的测量。虽然这些肯定是预测抓握的鲁棒性的重要因素，但是它们不携带关于执行抓握所需的到达动作的可行性的信息。基于我们对物理拾取实验的观察，我们认为拾取任务的执行成功部分取决于到达运动的容易程度。我们提出了我们的度量，它结合了2个措施，涉及手臂运动学和现有的手启发式度量。模拟结果以及在我们的机器人，克莱顿，物理实验。
In this paper we propose an approach to robot grasp prioritization based on a combined arm-and-hand metric. Most traditional approaches evaluate grasps based on hand-centric metrics such as force-closure, finger spread, contact surface area and similar measures. While these are certainly important factors to predict the robustness of a grasp, they do not carry information on the feasibility of the reaching action needed to execute the grasp. Based on our observations of physical pick-up experiments, we suggest that the execution success of a pick-up task is partially dependant on the easiness of the reaching movement. We present our metric, which combines 2 measures involving arm-kinematics and an existing hand heuristic metric. Results of simulated as well as physical experiments in our robot, Crichton, are presented.