A Novel Telelocomotion Framework with CoM Estimation for Scalable Locomotion on Humanoid Robots

Teleoperated humanoid robot systems have made substantial advancements in recent years, offering a physical avatar that harnesses human skills and decision-making while safeguarding users from hazardous environments. However, current telelocomotion interfaces often fail to accurately represent the robot’s environment, limiting the user’s ability to effectively navigate the robot through unstructured terrain. This paper presents an initial telelocomotion framework that integrates the ForceBot locomotion interface with the smallsized humanoid robot, HECTOR V2. The framework utilizes ForceBot to simulate walking motion and estimate the user’s Center of Mass (CoM) trajectory, which serves as a tracking reference for the robot. On the robot side, a model predictive control (MPC) approach, based on a reduced-order single rigid body model, is employed to track the user’s scaled trajectory. We present experimental results on ForceBot’s CoM estimation and the robot’s tracking performance, demonstrating the feasibility of this approach.