Soft Tracking Using Contacts for Cluttered Objects to Perform Blind Object Retrieval
Soft Tracking Using Contacts for Cluttered Objects to Perform Blind Object Retrieval
复制标题
DOI：
10.1109/lra.2022.3146915
复制
发表时间：
2022-01
影响因子：
5.2
通讯作者：
Sheng Zhong;Nima Fazeli;D. Berenson
中科院分区：
文献类型：
--
作者：
Sheng Zhong;Nima Fazeli;D. Berenson
从诸如橱柜、冰箱或垃圾箱之类的杂乱空间中检索对象需要以有限或没有视觉感测来跟踪对象。在这些场景中，接触反馈对于估计对象的姿态是必要的，然而对象是可移动的，而它们的形状和数量可能是未知的，使得接触与对象的关联极其困难。虽然以前的工作集中在多目标跟踪，其中的假设禁止使用先前的方法与接触式传感模态。相反，本文提出的方法软跟踪使用接触杂乱的对象（STUCCO），跟踪接触点的位置和隐式的对象关联使用粒子滤波器的信念。这允许在新信息变得可用时修改过去联系人的模糊对象关联。我们应用STUCCO盲对象检索问题，其中已知形状，但未知的姿态的目标对象必须从杂波中检索。我们的研究结果表明，我们的方法优于基线在四个模拟环境和一个真实的机器人，接触传感是嘈杂的。
Retrieving an object from cluttered spaces such as cupboards, refrigerators, or bins requires tracking objects with limited or no visual sensing. In these scenarios, contact feedback is necessary to estimate the pose of the objects, yet the objects are movable while their shapes and number may be unknown, making the association of contacts with objects extremely difficult. While previous work has focused on multi-target tracking, the assumptions therein prohibit using prior methods with just the contact-sensing modality. Instead, this paper proposes the method Soft Tracking Using Contacts for Cluttered Objects (STUCCO) that tracks the belief over contact point locations and implicit object associations using a particle filter. This allows ambiguous object associations of past contacts to be revised as new information becomes available. We apply STUCCO to the Blind Object Retrieval problem, where a target object of known shape but unknown pose must be retrieved from clutter. Our results suggest that our method outperforms baselines in four simulation environments and on a real robot, where contact sensing is noisy.