机器人通过学习人类操作数据，实现自然协作式物品交接。
Collaborative Object Handover in a Robot Crafting Assistant
- 基于人类远程操控数据训练协作交接模型
- 实验表明自主策略可实现有效协作交接
- 适合人机协同场景中的机器人交互设计
机器人正越来越多地与人类共同工作，如在餐厅送餐或装配线协助作业。这些场景常涉及人机之间的物品交接。为实现安全高效的人机协作（HRC），需在机器人的交接策略中融入人类上下文。本文基于自然手工任务中收集的人类远程操控数据，构建了协作式交接模型。通过在训练数据集上进行交叉验证及在相同HRC手工任务中的用户研究，比较了自主交接策略与人工遥控交接的表现。结果显示，自主策略能成功实现协作交接；但与人工操控相比，仍存在改进空间。
原文摘要 · Abstract (English)
Robots are increasingly working alongside people, delivering food to patrons in restaurants or helping workers on assembly lines. These scenarios often involve object handovers between the person and the robot. To achieve safe and efficient human-robot collaboration (HRC), it is important to incorporate human context in a robot's handover strategies. We develop a collaborative handover model trained on human teleoperation data collected in a naturalistic crafting task. To evaluate its performance, we conduct cross-validation experiments on the training dataset as well as a user study in the same HRC crafting task. The handover episodes and user perceptions of the autonomous handover policy were compared with those of the human teleoperated handovers. While the cross-validation experiment and user study indicate that the autonomous policy successfully achieved collaborative handovers, the comparison with human teleoperation revealed avenues for further improvements.
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