论文标题
积极的纠缠使随机的拓扑抓取
Active entanglement enables stochastic, topological grasping
论文作者
论文摘要
在生物学和工程机制中,抓握可以对抓地力和对象形态以及感知和运动计划高度敏感。在这里,我们通过使用一系列流体分流的空心弹性细丝来避免需要反馈或精确计划,以积极地与几何和拓扑复杂性不同的物体纠缠。由此产生的随机相互作用可以在大小,重量和形状变化的一系列目标对象上建立独特的柔软且符合的抓握策略。我们通过实验评估策略的抓地力,并使用一个计算框架来与柔性细丝的集体机制与复杂物体接触以解释我们的发现。总体而言,我们的研究强调了通过不受控制的空间分布方案的灯丝阵列的积极集体纠缠如何为软,适应性握把提供新的选择。
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 new options for soft, adaptable grasping.