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

TL;DR
This paper introduces a contact-based method for directly transferring grasps and manipulations between objects and robotic hands, enabling quick, user-controlled, and model-free synthesis of feasible hand poses, including on prosthetics.
Contribution
The method uniquely preserves contact shapes without relying on grasp families or training, and allows user control, making it adaptable and efficient for various robotic manipulation tasks.
Findings
Capable of synthesizing kinematically feasible hand poses in seconds.
Effective in response to design changes and in in-hand manipulation sequences.
Successfully demonstrated on a custom prosthetic hand.
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…
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Taxonomy
TopicsRobot Manipulation and Learning · Muscle activation and electromyography studies · Hand Gesture Recognition Systems
