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MANIPULATION

Contact Transfer: A Direct, User-Driven Method for Human to Robot Transfer of Grasps and Manipulations

Arjun Lakshmipathy, Dominik Bauer, Cornelia Bauer, Nancy S. Pollard

Year
2022
Citations
8

Abstract

We present a novel method for the direct transfer of grasps and manipulations between objects and hands through utilization of contact areas. Our method fully preserves contact shapes, and in contrast to existing techniques, is not dependent on grasp families, requires no model training or grasp sampling, makes no assumptions about manipulator morphology or kinematics, and allows user control over both transfer parameters and solution optimization. Despite these accommodations, we show that our method is capable of synthesizing kinematically-feasible whole hand poses in seconds even for poor initializations or hard-to-reach contacts. We additionally highlight the method's benefits in both response to design alterations as well as fast approximation over in-hand manipulation sequences. Finally, we demonstrate a solution generated by our method on a physical, custom-designed prosthetic hand.

Keywords

GRASPKinematicsComputer scienceRobotTransfer (computing)Artificial intelligenceControl engineeringGrippersControl theory (sociology)Control (management)

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