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In this paper, we propose a method for estimating in-hand object poses usingproprioception and tactile feedback from a bimanual robotic system. Our methodaddresses the problem of reducing pose uncertainty through a sequence offrictional contact interactions between the grasped objects. As part of ourmethod, we propose 1) a tool segmentation routine that facilitates contactlocation and object pose estimation, 2) a loss that allows reasoning oversolution consistency between interactions, and 3) a loss to promote convergingto object poses and contact locations that explain the external force-torqueexperienced by each arm. We demonstrate the efficacy of our method in atask-based demonstration both in simulation and on a real-world bimanualplatform and show significant improvement in object pose estimation over singleinteractions. Visit www.mmintlab.com/multiscope/ for code and videos.

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