Human sit-to-stand transfer modeling for optimal control of assistive robots

Sit-to-stand (STS) transfers are a common human task which involves very complex sensorimotor processes to control the highly nonlinear musculoskeletal system. In this paper, typical unassisted and assisted human STS transfers are formulated as optimal feedback control problem that finds a compromise between task end-point accuracy, human balance, jerk, effort, and torque change and takes further human biomechanical control constraints into account. Differential dynamic programming is employed, which allows taking the full, nonlinear human dynamics into consideration. The biomechanical dynamics of the human is modeled by a six link rigid body including leg, trunk and arm segments. Accuracy of the proposed modelling approach is evaluated for different human healthy subjects by comparing simulations and experimentally collected data. Acceptable model accuracy is achieved with a generic set of constant weights that prioritize the different criteria. The proposed STS model is finally used to determine optimal assistive strategies to be performed by a robotic mobility assistant suitable for either a person with specific body segment weakness or a more general weakness.