根据物体重量调整机器人交接动作，让交互更自然安全。
Impact of Object Weight in Handovers: Inspiring Robotic Grip Release and Motion from Human Handovers
- 分析人类交接时不同重量物体的行为，设计自适应抓握释放策略。
- 新数据集包含多种重量物体，验证了策略在自然度与效率上的提升。
- 适合人机协作场景，尤其关注物体重量变化的智能机器人研发。
本研究探讨物体重量对人类交接过程中运动与抓握释放的影响，旨在提升机器人与人类交互的自然性、安全性和效率。通过分析人类在不同重量物体交接中的行为模式，提出一种自适应机器人抓握释放策略，并构建了包含多种重量物体的交接数据集，包括YCB手交数据集。该研究还评估了基于人类行为的自适应机器人策略在人机交接中的表现，结果表明其在自然性、效率和用户感知方面均优于基线方法。
原文摘要 · Abstract (English)
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.
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