Softness-Adaptive Pinch-Grasp Strategy Using Fingertip Tactile Information of Robot Hand

Authors
Park, SungwooHwang, Donghyun
Issue Date
2021-10
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE ROBOTICS AND AUTOMATION LETTERS, v.6, no.4, pp.6370 - 6377
Abstract
We develop a tactile information-based pinch-grasp strategy enabling a robot hand to adaptively grasp easily deformable soft objects. When a robot hand has to perform grasping tasks, the grasp planner develops the grasping strategy based on visual information. However, the intrinsic properties of the target object, such as softness, cannot be detected appropriately using only visual feedback. To overcome this fundamental limitation, we aim to develop a softness-adaptive pinch-grasp strategy using fingertip tactile information. To achieve this, we first categorize soft objects based on the characteristic of resistance to deformation. Moreover, we design a three-dimensional tactile sensor that provides tactile information by measuring and localizing the distributed forces induced on its fingertip. In devising the adaptive grasp strategy, we focus on developing an algorithm that enables a robot hand to grasp soft objects by minimizing object deformation by controlling the pinch force based on the tactile feedback. The experimental results demonstrate that object deformation can be reduced by up to approximately 83.5% by the proposed strategy.
Keywords
SENSOR; FORCE; SKIN; USKIN; SENSOR; FORCE; SKIN; USKIN; Multifingered hands; grasping; tactile sensors; softness-adaptive grasp strategy
ISSN
2377-3766
URI
https://pubs.kist.re.kr/handle/201004/116356
DOI
10.1109/LRA.2021.3092770
Appears in Collections:
KIST Article > 2021
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