We introduce a new simulation benchmark "HandoverSim" for human-to-robot object handovers. To simulate the giver's motion, we leverage a recent motion capture dataset of hand grasping of objects. We create training and evaluation environments for the receiver with standardized protocols and metrics. We analyze the performance of a set of baselines and show a correlation with a real-world evaluation. Code is open sourced at https://handover-sim.github.io.
翻译:我们引入一个新的模拟基准“HandoverSim ”, 用于人类对机器人物体的交接。 为了模拟授标者的动作, 我们利用最近运动获取的关于手抓物体的数据集。 我们为接收者创造有标准化协议和指标的培训和评估环境。 我们分析一套基线的性能, 并显示与现实世界评估的相关性。 代码可以在 https://handover- sim.github.io 上公开发布 。