Towards Immersive Teleoperation: Dynamic Identification for Force Feedback of a Wearable Exoskeleton

Force-feedback haptic interfaces serve as vital tools in enhancing task execution during teleoperation. Wearable exoskeletons, as one of the haptic devices, provide a uniquely intuitive interface by directly translating operators’ motions to remote robots. Additionally, it is of great significance to obtain a precise dynamic model, a fundamental aspect for optimizing the force feedback function of the exoskeleton. Traditional methods like CAD modeling and heuristic techniques, while common, often introduce inaccuracies and complexities. This paper introduces a holistic system dynamic identification method, incorporating an optimized exciting trajectory. Through the application of a least-squares damping algorithm, we attain feasible parameters for the trajectory, ensuring accuracy and efficiency. Experimental simulations with the exoskeleton validate the practicality of the entire system identification method. Furthermore, comparative experiments, utilizing different trajectories, underscore the efficacy of the proposed Fourier series-based trajectory. The results highlight not only the feasibility of the method but also its potential to significantly advance the field of wearable exoskeletons and force feedback in teleoperation.