Using Collocated Vision and Tactile Sensors for Visual Servoing and Localization
Using Collocated Vision and Tactile Sensors for Visual Servoing and Localization
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DOI：
10.1109/lra.2022.3146565
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发表时间：
2022-04-01
影响因子：
5.2
通讯作者：
Atkeson, Christopher G.
中科院分区：
文献类型：
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作者：
Chaudhury, Arkadeep Narayan;Man, Timothy;Atkeson, Christopher G.
通过将相机与触觉传感器并置来协调接近度和触觉成像可以：1）在接触前提供有用信息，例如物体姿态估计，并与头戴式或外部深度相机相比，以更少的遮挡和更高的分辨率对机器人进行视觉伺服以对准目标；2）简化接触点和姿态估计问题，并在表面没有明显纹理或有许多可能匹配的重复纹理时帮助触觉传感避免错误匹配；3）利用触觉成像进一步细化接触点和物体姿态估计。我们用比标准操作数据集中大多数物体具有更多表面纹理的物体展示了我们的结果。我们了解到，光流需要在相机大量移动过程中进行积分，才能对预测运动方向有用。最重要的是，我们还了解到，除非能从并置的相机中获得合理的先验信息，否则最先进的视觉算法在物体模型上定位触觉图像的效果不佳。
Coordinating proximity and tactile imaging by collocating cameras with tactile sensors can 1) provide useful information before contact such as object pose estimates and visually servo a robot to a target with reduced occlusion and higher resolution compared to head-mounted or external depth cameras, 2) simplify the contact point and pose estimation problems and help tactile sensing avoid erroneous matches when a surface does not have significant texture or has repetitive texture with many possible matches, and 3) use tactile imaging to further refine contact point and object pose estimation. We demonstrate our results with objects that have more surface texture than most objects in standard manipulation datasets. We learn that optic flow needs to be integrated over a substantial amount of camera travel to be useful in predicting movement direction. Most importantly, we also learn that state of the art vision algorithms do not do a good job localizing tactile images on object models, unless a reasonable prior can be provided from collocated cameras.