抓住
工作区
稳健性(进化)
计算机科学
执行机构
夹持器
机械手
人工智能
适应性
计算机视觉
贴片设备
控制工程
机器人
模拟
工程类
机械工程
程序设计语言
基因
化学
生物
生物化学
生态学
作者
Aaron M. Dollar,Robert D. Howe
标识
DOI:10.1177/0278364909360852
摘要
The inherent uncertainty associated with unstructured environments makes establishing a successful grasp difficult. Traditional approaches to this problem involve hands that are complex, fragile, require elaborate sensor suites, and are difficult to control. Alternatively, by carefully designing the mechanical structure of the hand to incorporate features such as compliance and adaptability, the uncertainty inherent in unstructured grasping tasks can be more easily accommodated. In this paper, we demonstrate a novel adaptive and compliant grasper that can grasp objects spanning a wide range of size, shape, mass, and position/orientation using only a single actuator. The hand is constructed using polymer-based Shape Deposition Manufacturing (SDM) and has superior robustness properties, making it able to withstand large impacts without damage. We also present the results of two experiments to demonstrate that the SDM Hand can reliably grasp objects in the presence of large positioning errors, while keeping acquisition contact forces low. In the first, we evaluate the amount of allowable manipulator positioning error that results in a successful grasp. In the second experiment, the hand autonomously grasps a wide range of spherical objects positioned randomly across the workspace, guided by only a single image from an overhead camera, using feed-forward control of the hand.
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