Predictive Human-in-the-Loop Simulations for Assistive Exoskeletons

摘要

Abstract Design and evaluation of exoskeletons is often a time consuming and costly process that involves prototyping, human testing, and multiple design iterations. For active exoskeletons, the primary challenge is to detect the wearer’s movement intent and provide potent assistance, which often requires sophisticated control algorithms. The goal of this study is to integrate human musculoskeletal models with robot modeling and control for virtual human-in-the-loop evaluation of exoskeleton design and control. We present potential strategies for assisting various human motions such as squatting, lifting, walking, and running. Several exoskeleton designs (for back, upper extremity, and lower extremity) and their control methods are evaluated with an integrated human-in-the-loop simulation approach to study their functionalities and biomechanical effects on the wearer’ musculoskeletal system. We hope this simulation paradigm can be utilized for virtual design and evaluation of exoskeletons and pave the way to build or optimize exoskeletons.