This article presents a human–robot cooperation controller towards the lower extremity
exoskeleton which aims to improve the tracking performance of the exoskeleton and reduce
the human–robot interaction force. Radial basis function neural network is introduced to
model the human–machine interaction which can better approximate the non-linear
relationship than the general impedance model. A new method to calculate the inverse
Jacobian matrix is presented. Compared to traditional damped least squares method, the …

This article introduces a human–robot interaction controller toward the lower extremity
exoskeleton whose aim is to improve the tracking performance and drive the exoskeleton to
shadow the wearer with less interaction force. To acquire the motion intention of the wearer,
two subsystems are designed: the first is to infer the wearer is in which phase based on floor
reaction force detected by a multi-sensor system installed in the sole, and the second is to
infer the motion velocity based on the multi-axis force sensor and admittance model. An …