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

Bipasha Sen, Michelle Wang, Nandini Thakur, Aditya Agarwal, Pulkit Agrawal

Keywords: teleoperation, mobile manipulation, active perception, actuated neck, full body control, imitation learning

Abstract: 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.

Submission Number: 31