Human-in-the-loop layered architecture for control of a wearable ankle–foot robot

Abstract

Intelligent wearable robotics is a promising approach for the development of devices that can interact with people and assist them in daily activities. This work presents a novel human-in-the-loop layered architecture to control a wearable robot while interacting with the human body. The proposed control architecture is composed of high-, mid- and low-level computational and control layers, together with wearable sensors, for the control of a wearable ankle–foot robot. The high-level layer uses Bayesian formulation and a competing accumulator model to estimate the human posture during the gait cycle. The mid-level layer implements a Finite State Machine (FSM) to prepare the control parameters for the wearable robot based on the decisions from the high-level layer. The low-level layer is responsible for the precise control of the wearable robot over time using a cascade proportional–integral–derivative (PID) control approach. The human-in-the-loop layered architecture is systematically validated with the control of a 3D printed wearable ankle–foot robot to assist the human foot while walking. The assistance is applied lifting up the human foot when the toe-off event is detected in the walking cycle, and the assistance is removed allowing the human foot to move down and contact the ground when the heel-contact event is detected. Overall, the experiments in offline and real-time modes, undertaken for the validation process, show the potential of the human-in-the-loop layered architecture to develop intelligent wearable robots capable of making decisions and responding fast and accurately based on the interaction with the human body.