共形矩阵
量子纠缠
计算机科学
拓扑(电路)
对象(语法)
蛋白质丝
生物系统
人工智能
分布式计算
理论计算机科学
纳米技术
物理
工程类
材料科学
生物
量子
量子力学
电气工程
复合材料
作者
Kaitlyn P. Becker,Clark Teeple,Nicholas Charles,Yeonsu Jung,Daniel Baum,James C. Weaver,Lakshminarayanan Mahadevan,Robert J. Wood
标识
DOI:10.1073/pnas.2209819119
摘要
Grasping, in both biological and engineered mechanisms, can be highly sensitive to the gripper and object morphology, as well as perception and motion planning. Here, we circumvent the need for feedback or precise planning by using an array of fluidically actuated slender hollow elastomeric filaments to actively entangle with objects that vary in geometric and topological complexity. The resulting stochastic interactions enable a unique soft and conformable grasping strategy across a range of target objects that vary in size, weight, and shape. We experimentally evaluate the grasping performance of our strategy and use a computational framework for the collective mechanics of flexible filaments in contact with complex objects to explain our findings. Overall, our study highlights how active collective entanglement of a filament array via an uncontrolled, spatially distributed scheme provides options for soft, adaptable grasping.
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