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English(EN) Tactile-Proprioceptive Sensor Fusion for Contact Wrench Estimation in Whole-Body Physical Human-Robot Interaction

新的传感器融合框架增强了机器人交互

研究人员开发了一个新的触觉-本体感觉传感器融合框架,以增强物理人机交互。该方法结合了来自气动皮肤垫的触觉数据和基于电机电流的本体感觉,以准确估计机器人上的多轴接触力。利用时间卷积网络(TCN)来管理摩擦滞后,确保运动过程中机器人引导的平稳性和响应性。该系统已在集成皮肤的机器人手臂上得到验证,与仅依赖触觉或本体感觉数据的系统相比,显示出更高的灵敏度和响应性。 AI

排序理由 该集群包含一篇详细介绍机器人新技术框架的研究论文。

在 arXiv cs.LG 阅读 →

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新的传感器融合框架增强了机器人交互

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Junha Min, Junghyeon Ma, Jiwung Kwon, Sunggyu Bae, Joohyung Kim, Kyungseo Park ·

    用于全身物理人机交互中接触力矩估计的触觉-本体感觉传感器融合

    arXiv:2605.28412v1 Announce Type: cross Abstract: Direct physical guidance is a natural means of teaching and interacting with robots, and robotic skins make a key contribution by enabling sensitive contact sensing and localization. This paper presents a tactile-proprioceptive se…

  2. arXiv cs.LG TIER_1 English(EN) · Kyungseo Park ·

    用于全身物理人机交互中接触力矩估计的触觉-本体感觉传感器融合

    Direct physical guidance is a natural means of teaching and interacting with robots, and robotic skins make a key contribution by enabling sensitive contact sensing and localization. This paper presents a tactile-proprioceptive sensor fusion framework for natural physical human-r…