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        <title>Talk by Lilian Briaut on his implementation of the DexUmi exoskeleton for the H1-v2 robot.</title>
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        <description>This talk presents the design, implementation, and critical analysis of a real-time bimanual teleoperation system for the Unitree H1-2 humanoid robot, as well as the creation and establishment of a protocol for building a dataset from scratch. The operator controls both arms (7 degrees of freedom each) through their own wrist movements, captured by a Qualisys optical motion capture system, while the Inspire Hands are teleoperated via a hand exoskeleton worn by the same user. The software pipeline developed converts Cartesian targets into joint commands via differential inverse kinematics (Pinocchio + Pink), backed by a multi-layer safety architecture: adaptive 1€ filtering, a temporal buffer, and kinematic bounds built into the IK. The integration of the Inspire Hands (6 DoF) opens the way to data collection for object manipulation with a humanoid robot — a task more complicated than it appears. A real incident — the robot's fall on June 3, 2026 — showed that an overly abrupt arm command is enough to destabilize a balance controller that had never encountered this case during training. The rest of the work therefore focused on the robustness of the teleoperation, then on setting up the collection pipeline: synchronized recording of states, commands, tactile data, and three video streams, episode segmentation, and export in LeRobot format. As a side project, a comparison between inverse kinematics, reinforcement learning, and residual learning was carried out as supplementary work, for my own personal interest.</description>
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            <title>Talk by Lilian Briaut on his implementation of the DexUmi exoskeleton for the H1-v2 robot.</title>
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