Data-Driven Predictive Control for Robust Exoskeleton Locomotion

Exoskeleton locomotion must be robust while being adaptive to different users with and without payloads. To address these challenges, this work introduces a data-driven predictive control (DDPC) framework to synthesize walking gaits for lower-body exoskeletons, employing Hankel matrices and a state transition matrix for its data-driven model. The proposed approach leverages DDPC through a multi-layer architecture. At the top layer, DDPC serves as a planner employing Hankel matrices and a state transition matrix to generate a data-driven model that can learn and adapt to varying users and payloads. At the lower layer, our method incorporates inverse kinematics and passivity-based control to map the planned trajectory from DDPC into the full-order states of the lower-body exoskeleton. We validate the effectiveness of this approach through numerical simulations and hardware experiments conducted on the Atalante lower-body exoskeleton with different payloads. Moreover, we conducted a comparative analysis against the model predictive control (MPC) framework based on the reduced-order linear inverted pendulum (LIP) model. Through this comparison, the paper demonstrates that DDPC enables robust bipedal walking at various velocities while accounting for model uncertainties and unknown perturbations.

Authors

• Kejun Li
• Jeeseop Kim
• Xiaobin Xiong
• Kaveh Akbari Hamed
• Yisong Yue
• Aaron D. Ames

Keywords

• Adaptation models
• Analytical models
• Perturbation methods
• Exoskeletons
• Predictive models
• Hardware
• Trajectory
• Numerical models
• Predictive control
• Payloads
• Data-driven Predictive Control
• Numerical Simulations
• Model Predictive Control
• Data-driven Models
• Inverse Kinematics
• State Transition Matrix
• Inverted Pendulum
• Hardware Experiments
• Inverted Pendulum Model
• Actuator
• Center Of Pressure
• Single Domain
• Asteraceae
• Representation Of System
• Vertical Position
• Step Length
• Tracking Performance
• Quadratic Programming
• Trajectories Of System
• Low-level Control
• Bipedal Locomotion
• Input Trajectory
• Nominal Trajectory
• Trajectory Planning
• Reduced-order Model
• Continuum Mechanics
• Quadruped Robot
• Trajectory Optimization
• Control Horizon