Impact of Object Weight in Handovers: Inspiring Robotic Grip Release and Motion from Human Handovers

Fuente: arXiv
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Autori principali: Khanna, Parag, Björkman, Mårten, Smith, Christian
Natura: Preprint
Pubblicazione: 2025
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author Khanna, Parag
Björkman, Mårten
Smith, Christian
author_facet Khanna, Parag
Björkman, Mårten
Smith, Christian
contents This work explores the effect of object weight on human motion and grip release during handovers to enhance the naturalness, safety, and efficiency of robot-human interactions. We introduce adaptive robotic strategies based on the analysis of human handover behavior with varying object weights. The key contributions of this work includes the development of an adaptive grip-release strategy for robots, a detailed analysis of how object weight influences human motion to guide robotic motion adaptations, and the creation of handover-datasets incorporating various object weights, including the YCB handover dataset. By aligning robotic grip release and motion with human behavior, this work aims to improve robot-human handovers for different weighted objects. We also evaluate these human-inspired adaptive robotic strategies in robot-to-human handovers to assess their effectiveness and performance and demonstrate that they outperform the baseline approaches in terms of naturalness, efficiency, and user perception.
format Preprint
id arxiv_https___arxiv_org_abs_2502_17834
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Impact of Object Weight in Handovers: Inspiring Robotic Grip Release and Motion from Human Handovers
Khanna, Parag
Björkman, Mårten
Smith, Christian
Robotics
Human-Computer Interaction
This work explores the effect of object weight on human motion and grip release during handovers to enhance the naturalness, safety, and efficiency of robot-human interactions. We introduce adaptive robotic strategies based on the analysis of human handover behavior with varying object weights. The key contributions of this work includes the development of an adaptive grip-release strategy for robots, a detailed analysis of how object weight influences human motion to guide robotic motion adaptations, and the creation of handover-datasets incorporating various object weights, including the YCB handover dataset. By aligning robotic grip release and motion with human behavior, this work aims to improve robot-human handovers for different weighted objects. We also evaluate these human-inspired adaptive robotic strategies in robot-to-human handovers to assess their effectiveness and performance and demonstrate that they outperform the baseline approaches in terms of naturalness, efficiency, and user perception.
title Impact of Object Weight in Handovers: Inspiring Robotic Grip Release and Motion from Human Handovers
topic Robotics
Human-Computer Interaction
url https://arxiv.org/abs/2502.17834