English(EN) A Model-based Visual Contact Localization and Force Sensing System for Compliant Robotic Grippers

机器人夹爪利用人工智能驱动的视觉传感进行精确力估计

作者 PulseAugur 编辑部 · [2 个来源] · 2026-05-01 00:34

研究人员开发了一种新颖的基于模型的系统，利用RGB-D相机的视觉反馈来估计机器人夹爪中的抓取力。该方法集成了迭代接触定位和逆有限元分析模拟，使其能够泛化到未见过的物体和条件。该系统表现出高精度，在加载阶段的平均均方根误差为0.23 N，在整个抓取过程中的误差为4.34%。 AI

影响通过实现精确的间接力传感，提高了机器人操作的安全性与可控性。

排序理由学术论文，详细介绍了一种用于机器人夹爪的新系统。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv cs.CV TIER_1 English(EN) · Kaiwen Zuo, Shuyuan Yang, Zonghe Chua · 2026-05-04 04:00

A Model-based Visual Contact Localization and Force Sensing System for Compliant Robotic Grippers

arXiv:2605.00307v1 Announce Type: cross Abstract: Grasp force estimation can help prevent robots from damaging delicate objects during manipulation and improve learning-based robotic control. Integrating force sensing into deformable grippers negotiates trade-offs in cost, comple…
arXiv cs.CV TIER_1 English(EN) · Zonghe Chua · 2026-05-01 00:34

A Model-based Visual Contact Localization and Force Sensing System for Compliant Robotic Grippers

Grasp force estimation can help prevent robots from damaging delicate objects during manipulation and improve learning-based robotic control. Integrating force sensing into deformable grippers negotiates trade-offs in cost, complexity, mechanical robustness, and performance. With…