Continuous in-hand rotation requires coordinated contact maintenance and renewal, linking manipulation performance to both hand geometry and tactile feedback. We investigate these relationships through rotational progress, finger participation, and fingertip loading on two versions of the low-cost LEAP Hand with anthropomorphic and symmetric finger arrangements. Both hands are integrated with TacTip vision-based tactile sensors and use a shared reinforcement learning framework. Simulation evaluates full tactile, binary touch, and proprioception-only observations on 12 unseen objects; hardware experiments evaluate full tactile policies on ten objects under multiple hand orientations. In simulation, full tactile observations increase mean normalized rotation per episode over proprioception alone by 94.8% for the anthropomorphic hand and 66.9% for the symmetric hand, with longer mean episode durations and lower mean total fingertip loads. Hardware contact measurements reveal more differentiated finger participation in the anthropomorphic hand, while cumulative loading is more evenly distributed across the symmetric hand's fingers. Overall, the symmetric hand achieves a 32.0% higher mean rotation count and a 25.8% higher aggregate rotation rate, together with longer manipulation duration. Additional hardware force recordings show a 19.9% lower mean total fingertip load for this layout. These findings relate finger arrangement to contact organization and load sharing, and show that richer tactile information supports greater task progress at lower mean loading in both simulated embodiments.

翻译：暂无翻译