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Learning to Look Around: Enhancing Teleoperation and Learning with a Human-like Actuated Neck

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arxiv 2411.00704 v1 pith:GFERZLNI submitted 2024-11-01 cs.RO

classification cs.RO
keywords actuatednecklearningteleoperationnaturalperceptionsystemtasks
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We introduce a teleoperation system that integrates a 5 DOF actuated neck, designed to replicate natural human head movements and perception. By enabling behaviors like peeking or tilting, the system provides operators with a more intuitive and comprehensive view of the environment, improving task performance, reducing cognitive load, and facilitating complex whole-body manipulation. We demonstrate the benefits of natural perception across seven challenging teleoperation tasks, showing how the actuated neck enhances the scope and efficiency of remote operation. Furthermore, we investigate its role in training autonomous policies through imitation learning. In three distinct tasks, the actuated neck supports better spatial awareness, reduces distribution shift, and enables adaptive task-specific adjustments compared to a static wide-angle camera.

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Cited by 1 Pith paper

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  1. Vision in Action: Learning Active Perception from Human Demonstrations

    cs.RO 2025-06 conditional novelty 6.0 of 10

    ViA trains bimanual manipulation policies from human demonstrations that include active head-camera movement, using a 6-DoF robot neck and a VR interface with point-cloud rendering, reporting large gains on three occl...

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