Dynamic Locomotion Teleoperation of a Wheeled Humanoid Robot Reduced Model with a Whole-Body Human-Machine Interface
This work addresses the challenge of dynamic bilateral teleoperation for humanoid robots, which is incremental in improving control interfaces for robotics applications.
The study tackled dynamic locomotion teleoperation for wheeled humanoid robots by developing a whole-body human-machine interface with force feedback and comparing velocity vs. acceleration mappings, finding that all subjects completed tasks after practice and force feedback improved performance, though preferences varied.
Bilateral teleoperation provides humanoid robots with human planning intelligence while enabling the human to feel what the robot feels. It has the potential to transform physically capable humanoid robots into dynamically intelligent ones. However, dynamic bilateral locomotion teleoperation remains as a challenge due to the complex dynamics it involves. This work presents our initial step to tackle this challenge via the concept of wheeled humanoid robot locomotion teleoperation by body tilt. Specifically, we developed a force-feedback-capable whole-body human-machine interface (HMI), and designed a force feedback mapping and two teleoperation mappings that map the human's body tilt to the robot's velocity or acceleration. We compared the two mappings and studied the force feedback's effect via an experiment, where seven human subjects teleoperated a simulated robot with the HMI to perform dynamic target tracking tasks. The experimental results suggest that all subjects accomplished the tasks with both mappings after practice, and the force feedback improved their performances. However, the subjects exhibited two distinct teleoperation styles, which benefited from the force feedback differently. Moreover, the force feedback affected the subjects' preferences on the teleoperation mappings, though most subjects performed better with the velocity mapping.