Control of Upper-Limb Power-Assist Exoskeleton Using a Human-Robot Interface Based on Motion Intention Recognition

Abstract

Recognition of the wearer's motion intention plays an important role in the study of power-assist robots. In this paper, an intention-guided control strategy is proposed and applied to an upper-limb power-assist exoskeleton. Meanwhile, a human-robot interface comprised of force-sensing resistors (FSRs) is designed to estimate the motion intention of the wearer's upper limb in real time. Moreover, a new concept called the “intentional reaching direction (IRD)” is proposed to quantitatively describe this intention. Both the state model and the observation model of IRD are obtained by studying the upper limb behavior modes and analyzing the relationship between the measured force signals and the motion intention. Based on these two models, the IRD can be inferred online using an adapted filtering technique. Guided by the inferred IRD, an admittance control strategy is deployed to control the motions of three DC motors placed at the corresponding joints of the robotic arm. The effectiveness of the proposed approaches is finally confirmed by experiments on a 3 degree-of-freedom (DOF) upper-limb robotic exoskeleton.