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DataGlove
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Dexterous manipulation research relies on demonstration data collected through teleoperation.[More]
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The recent collaboration between ABB Robotics and PSYONIC demonstrates how human-generated data is helping advance robot learning. As part of this workflow, MANUS gloves were used to capture natural hand movements that contribute to human demonstration data for robot training. Haply,as another part of the workflow, supports the wrist tracking and…[More]
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Robot world models predict how the world changes in response to actions, supporting applications like teleoperation, policy evaluation, and model-based planning. For dexterous robotics, this is complicated by limited robot data and scarce action labels, since collecting robot trajectories is costly and hardware variation restricts scenario covera…[More]
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BMW Group Plant Landshut is expanding its work in physical AI, taking on central software development for AI-supported robotics in component production. The plant's demonstration-based learning workflow uses MANUS data gloves to capture the dexterous manipulation data that trains its humanoid robotic systems.[More]
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ROBOTERA XHAND 1 Pro combines 21 active degrees of freedom with a fully actuated architecture and tactile sensing distributed across the entire hand surface. This combination of joint-level control and dense contact sensing supports complex grasping, in-hand manipulation, and reinforcement learning research. These applications require both precis…[More]
