Predictive Optimization of Assistive Force in Admittance Control-Based Physical Interaction for Robotic Gait Assistance

Abstract

In this letter, we introduce our approach to walking assistance for elderly adults through predictive optimization of gait assistive force. We focus on providing supportive interaction force to the user during walking with a robotic assistive device with an admittance controlled mobile base. Appropriate physical human-robot interaction (pHRI) could be beneficial in reducing the risk associated with immobility such as disuse syndrome by encouraging physical activities with proper assistance. We propose an optimization algorithm based on a model predictive control approach in order to provide desirable assistive forces according to the estimated user's state during walking. Using a simplified human gait model with a linear inverted pendulum, we formulate the optimization of the assistive forces as a linear quadratic programming problem that can be suitable for real-time pHRI. Numerical simulations and experimental results demonstrate the feasibility of our gait support strategy in achieving appropriate compliant interactions during walking, fall prevention, and suitable positioning for user companion.