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A Soft Enveloping Gripper with Enhanced Grasping Ability via Morphological Adaptability

Yufei Hao, Zhongkui Wang, Yuzhao Zhou, Weitai Zhou, Tengfei Cai, Jianhua Zhang, Fuchun Sun

发表年份
2023
引用次数
19
访问权限
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摘要

Hitherto, automated grasping with robotic grippers requires adjusting the posture and force of the fingers based on the size, geometry, stiffness, and pose of the objects. To provide a simpler but efficient grasping methodology, a soft enveloping gripper is presented and investigated how its morphological adaptability improves the grasping ability by comparing its performance with fingered grippers. Results show that this enveloping gripper can omnidirectionally envelop objects via active–passive interaction, which allows the gripper to 100% grasp the object located at different positions within range and keep their orientations. However, the grasping success rate and orientation error of the fingered grippers highly depend on the relative position and angle of the objects to the grippers, as well as the number of fingers. The dynamic vibration and decay time of the enveloping gripper when grasping a 500 g weight are, both, approximately one‐sixth of those of the two‐fingered gripper when grasping a 12.37 g cube. This enveloping gripper can automatically grasp objects (including deformable ones) lying in different poses without posture estimation and force control with a simple vision‐based automatic grasping method. The enveloping grasping method may open an avenue for simple, low cost yet powerful automatic grasping applications.

关键词

GrippersGRASPAdaptabilityArtificial intelligenceComputer visionStiffnessOrientation (vector space)Computer scienceObject (grammar)Engineering

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