arXiv:2501.06987cs.RO2025-01被引 1
用抓握质量指标检测手物接触，准确率近90%。
Hand-Object Contact Detection using Grasp Quality Metrics
- 通过手与物体姿态提取抓握质量指标
- 在DexYCB数据集上准确率接近90%
- 适合机器人交互与人机交接场景
我们提出一种基于抓握质量指标的手物接触检测系统，该指标从物体和手的姿态中提取，并在DexYCB数据集上进行评估。实验结果表明，该系统具有高精度（接近90%）。未来工作将聚焦于基于视觉估计的实时实现，并集成至机器人与人类之间的手递手系统中。
原文摘要 · Abstract (English)
We propose a novel hand-object contact detection system based on grasp quality metrics extracted from object and hand poses, and evaluated its performance using the DexYCB dataset. Our evaluation demonstrated the system's high accuracy (approaching 90%). Future work will focus on a real-time implementation using vision-based estimation, and integrating it to a robot-to-human handover system.
接触检测抓握质量机器人交互
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