重新审视铰接物体操作的本体感觉感知
Revisiting Proprioceptive Sensing for Articulated Object Manipulation
AI总结：
本文重新审视铰接物体操作中的本体感觉感知，构建了一个利用位置控制机器人和平行夹爪打开橱柜的系统，发现本体感觉在接触期间具有价值，并引发对其与视觉方法权衡的讨论。
摘要：
协助人类的机器人将需要与铰接物体（如橱柜或微波炉）进行交互。早期创建此类系统的工作在接触期间使用本体感觉来估计关节机制。然而，如今几乎所有系统都仅使用视觉，不再在接触期间考虑本体感觉信息。我们认为接触期间的本体感觉信息是宝贵的信息源，且在文献中未找到不使用它的明确动机。因此，本文创建了一个系统，从给定抓取开始，使用本体感觉感知，通过位置控制机器人和平行夹爪打开橱柜。我们对该系统进行了定性评估，发现夹爪与手柄之间的滑动限制了性能。尽管如此，我们发现该系统已经表现得相当好。这引发了一个问题：我们是否应该在铰接物体操作系统中更多地利用接触期间的本体感觉信息，还是不值得增加复杂性，仅靠视觉就能应对？我们对此没有答案，但希望能引发一些讨论。该系统的代码库和视频可在 https://tlpss.github.io/revisiting-proprioception-for-articulated-manipulation/ 获取。
英文摘要：
Robots that assist humans will need to interact with articulated objects such as cabinets or microwaves. Early work on creating systems for doing so used proprioceptive sensing to estimate joint mechanisms during contact. However, nowadays, almost all systems use only vision and no longer consider proprioceptive information during contact. We believe that proprioceptive information during contact is a valuable source of information and did not find clear motivation for not using it in the literature. Therefore, in this paper, we create a system that, starting from a given grasp, uses proprioceptive sensing to open cabinets with a position-controlled robot and a parallel gripper. We perform a qualitative evaluation of this system, where we find that slip between the gripper and handle limits the performance. Nonetheless, we find that the system already performs quite well. This poses the question: should we make more use of proprioceptive information during contact in articulated object manipulation systems, or is it not worth the added complexity, and can we manage with vision alone? We do not have an answer to this question, but we hope to spark some discussion on the matter. The codebase and videos of the system are available at https://tlpss.github.io/revisiting-proprioception-for-articulated-manipulation/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
