Inertially Significant Humanoid Teleoperation via Whole Body Model Predictive Control and Online Parameter Estimation
The research addresses how humanoid robots can effectively perform tasks while carrying heavy loads by sensing and adapting to changes in inertial parameters. It integrates a Whole Body Model Predictive Controller (WB-MPC) with an Extended Kalman Filter (EKF) to estimate these unknown physical properties online. This allows the controller to provide accurate feedforward torques, significantly improving dynamic balance and task performance under external loads.