Exoskeleton-covered soft finger with vision-based proprioception and exteroception
Exoskeleton-covered soft finger with vision-based proprioception and exteroception
复制标题
外骨骼覆盖的软手指，具有基于视觉的本体感觉和外感觉
DOI：
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
E. Adelson
中科院分区：
文献类型：
--
作者：
Y. She;Sandra Q. Liu;Peiyu Yu;E. Adelson
与传统的刚体机器人相比，软体机器人在适应性、安全性和灵活性方面具有显著的优势。然而，由于软机器人具有很高的灵活性和弹性，为其配备精确的本体感觉和外部感觉是一项具有挑战性的任务。在这项工作中，我们开发了一种新型的外骨骼覆盖的软手指，它具有嵌入式摄像头和深度学习方法，能够实现高分辨率的本体感知和丰富的触觉感知。为此，我们设计了沿手指轴向的特征，以实现高分辨率本体感知，并在手指表面加入反射墨水涂层，以实现丰富的触觉感知。我们设计了一种高度欠驱动的外骨骼，带有肌腱驱动的机构来驱动手指。最后，我们将两个手指组装在一起组成机器人夹持器，并成功地执行了需要形状和触觉信息的棒材分类任务。我们使用来自嵌入式传感器的数据来训练神经网络，用于本体感觉和形状(盒子与圆柱体)分类。CNN在我们的测试装置上具有99%以上的准确率(所有6个关节角度都在误差1美元以内)，在现场测试中平均累积距离误差为0.77 mm，优于人类手指本体感觉。这些技术为软机器人提供了同时感知其本体感知状态和周围环境的高级能力，为软机器人解决日常操作任务提供了潜在的解决方案。我们相信，本文提出的方法可以广泛应用于不同的设计和应用。
Soft robots offer significant advantages in adaptability, safety, and dexterity compared to conventional rigid-body robots. However, it is challenging to equip soft robots with accurate proprioception and exteroception due to their high flexibility and elasticity. In this work, we develop a novel exoskeleton-covered soft finger with embedded cameras and deep learning methods that enable high-resolution proprioceptive sensing and rich tactile sensing. To do so, we design features along the axial direction of the finger, which enable high-resolution proprioceptive sensing, and incorporate a reflective ink coating on the surface of the finger to enable rich tactile sensing. We design a highly underactuated exoskeleton with a tendon-driven mechanism to actuate the finger. Finally, we assemble 2 of the fingers together to form a robotic gripper and successfully perform a bar stock classification task, which requires both shape and tactile information. We train neural networks for proprioception and shape (box versus cylinder) classification using data from the embedded sensors. The proprioception CNN had over 99\% accuracy on our testing set (all six joint angles were within 1$^\circ$ of error) and had an average accumulative distance error of 0.77 mm during live testing, which is better than human finger proprioception. These proposed techniques offer soft robots the high-level ability to simultaneously perceive their proprioceptive state and peripheral environment, providing potential solutions for soft robots to solve everyday manipulation tasks. We believe the methods developed in this work can be widely applied to different designs and applications.
身体感知软机器人：本体感受和外感受传感器的集成
DOI：
10.1109/icra.2018.8463169
发表时间：
2018
期刊：
--
影响因子：
--
作者：
Soter G
通讯作者：
Soter G
DOI：
10.1109/icra.2018.8461110
发表时间：
2018-05
期刊：
2018 IEEE International Conference on Robotics and Automation (ICRA)
影响因子：
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作者：
Jennifer L. Molnar;Ching-An Cheng;Lucas O. Tiziani;Byron Boots;Frank L. Hammond
通讯作者：
Jennifer L. Molnar;Ching-An Cheng;Lucas O. Tiziani;Byron Boots;Frank L. Hammond
影响因子：
2.5
作者：
Fuentes, Christina T.;Bastian, Amy J.
通讯作者：
Bastian, Amy J.