In-hand assembly is constrained by the need to maintain grasps on two separate parts while controlling their relative motion within a single hand. To enable both in-hand assembly and manipulation, we present a reconfigurable dual-opposition architecture. Specifically, to support simultaneous grasping of two parts and coordinated in-hand manipulation, four independently actuated fingers are organized into two virtual finger (VF) oppositions, with their relative configuration controlled by a reconfigurable palm. To describe hand motion and simultaneous two-object grasping configurations, a kinematic model of the fingers and palm and an object-size-conditioned workspace formulation are built. To further evaluate motion performance and assembly capability, finger-joint motion and palm tracking are characterized, and in-hand assembly is demonstrated through tasks involving grasping, alignment, fastening, and pressing. Ablation experiments further demonstrate the importance of finger abduction/adduction and palm reconfiguration for successful in-hand assembly. In simulation, the proposed hand achieves a mean continuous sphere rotation success rate of 98.6% over diameters of 40-230 mm, compared with 73.8% for the LEAP Hand. After policy fine-tuning with external disturbances, the proposed hand achieves 92.8% success under disturbances from multiple directions, compared with 45.2% for the LEAP Hand. Hardware demonstrations further show in-hand rotation of objects of different sizes using policies trained in simulation. Together, these results show that the proposed architecture supports both assembly of two separately held parts and coordinated manipulation of a single object within one hand.
The Cartesian Hand is introduced, a 7-DoF end-effector that rethinks dexterous manipulation by combining independent grasping and relative manipulation within a single end-effector using only linear motion.
Bo-Xi Xia, Bo-Kuan Li, Ryan Shin et al.· 0 citations
A reinforcement learning formulation is presented to solve in-hand assembly: mating two rigid objects within a single dexterous hand, with no second arm and no fixture, which shows robustness to state-estimation errors caused by oc- clusion.
Liu-Ao Pei, Tian-Yue Wu, Hui Zhang et al.· 3 citations
Dexterous manipulation in confined spaces requires local control of hand orientation. Without a wrist, a dexterous hand must obtain this local orientation through coordinated motion of the robot arm, often involving several joints and a more complex end-effector path. We present CRAFT-Wrist, a concentric 2-DoF wrist ex...
Yu-Jie Pang, Sadman Sakib, M. A. Al Faruque· 0 citations
Dexterous robotic hands typically reproduce human hand morphology but inherit its one-sided grasping workspace, requiring wrist or arm reorientation to grasp from the opposite side. Existing reversible hands generally rely on non-anthropomorphic, soft, or task-specific finger arrangements, whereas conventional five-dig...
Chunghyeong Lee, Hyukjun Kwon, Sungeon Kim et al.· 0 citations
POISE (Palm-relative Object reaching In SE(3), a sim-to-real reinforcement learning framework for in-hand 6D object pose reaching, combines diverse stable-grasp initialization, goal- and geometry-conditioned control, an adaptive 6D goal curriculum, and a compact reward scheme for pose reaching and grasp preservation.
Jun-Xiao Lin, Tian-Yue Wu, Jie Yin et al.· 0 citations
A novel solution that integrates an active surface with underactuated compliance to achieve stable grasping of thin objects without complex control is proposed and can reliably complete long sequential “grasp-place” tasks.
Unknown authors· 0 citations
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