GPT-6.1 Sol参与活体小鼠脑手术：连续操作三次 定位误差减半

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GPT-6.1 Sol参与活体小鼠脑手术：连续操作三次 定位误差减半

机器人通过接触面的切向移动学习抓握

指尖压到物体时，除了有多深的压痕，物体有没有沿接触面滑动，也关系到机器人能否握稳。TactileLab研究团队在IsaacLab上搭建触觉仿真框架，用刚体模拟估计接触面上的密集切向运动，形成类似光流的触觉表示，并将它与接触深度一起输入控制策略。这样训练时可以获得剪切运动线索，也省去了逐次计算软体精细变形的负担。 Yijiong Lin等人的这项研究收录在11月6日更新的计算机科学预印本列表中。

为让模拟训练的策略用于真机，团队另行采集实际触觉传感器的图像，把图像流映射成与仿真相同的运动场和深度场。研究报告展示了双臂配合以及物体在灵巧手内移动等任务，并在不同传感器设计上检验这种映射。它所考察的是控制器如何利用接触反馈，而非单凭相机认出被抓的物体。

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