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We present our works in generation, recognition and editing of anthropomorphic motion using the stack of tasks framework. It is based on the task function formalism classically used for motion generation. The task spaces are suitable to perform motion analysis and task recognition because the tasks are described in those spaces. The reference behaviors are originated from human trajectories. Specific tasks are then integrated to retarget and to edit the reference motion in order to respect the dynamic constraints, the limits of the robot and the general aspect.
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