Predictive simulation for the design of robotic solution to mobility aid

Abstract

Abstract Maintaining substantial mobility is essential for those who suffer from reduced mobility to regain their independence in daily motion tasks. In recent years, robotic solutions to human mobility aid have been functionally verified by various applications. Moreover, with the emergence of new robots and systems, the robot design theory is also under rapid evolution. This paper proposes a methodology to enhance the design of robotic exoskeleton. The aim was to help the designer to select adequate dynamical behaviors to the development of control scheme for the human motions assisted by a robotic assistance device. The main contribution of this work resides in the proposition of optimized impedance parameters for a particular human movement via neuromusculoskeletal (NMS) modelization and predictive simulation. The technique of NMS modeling that represents the motions of human upper limb was applied to study the underlying mechanisms of human movements. Predictive simulation integrated with the NMS model was formulated and solved for generating a series of optimized human dynamic parameters. In this paper, a case study of human–robot interface has been proposed to exemplify our methodology. The modeling and simulation processes were validated with experimental tools. According to the simulated human dynamics, the optimized stiffness and damping coefficients of one degree of freedom were calculated. Results show that our methods are promising and allowed to specify the human movement for a given task, and can provide the design parameters to control scheme of a robotic exoskeleton.