MultiSCOPE: Disambiguating In-Hand Object Poses with Proprioception and Tactile Feedback

Andrea Sipos,Nima Fazeli

CoRR(2023)

引用 0|浏览9
暂无评分
摘要
In this paper, we propose a method for estimating in-hand object poses using proprioception and tactile feedback from a bimanual robotic system. Our method addresses the problem of reducing pose uncertainty through a sequence of frictional contact interactions between the grasped objects. As part of our method, we propose 1) a tool segmentation routine that facilitates contact location and object pose estimation, 2) a loss that allows reasoning over solution consistency between interactions, and 3) a loss to promote converging to object poses and contact locations that explain the external force-torque experienced by each arm. We demonstrate the efficacy of our method in a task-based demonstration both in simulation and on a real-world bimanual platform and show significant improvement in object pose estimation over single interactions. Visit www.mmintlab.com/multiscope/ for code and videos.
更多
查看译文
关键词
proprioception,object,feedback,in-hand
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要