Admittance swarm-based adaptive controller for lower limb exoskeleton with gait trajectory shaping

Abstract

The motivation for developing a rehabilitation lower-limb exoskeleton robot was to provide functional robot-assisted therapy for assisting physiotherapists in improving hemiplegic patients’ walking recovery. Rehabilitation tasks required robust and precise trajectory-tracking performance, mainly achieved with exoskeleton robots. This paper presents a study on the gait trajectory cycles of a rehabilitation lower-limb exoskeleton robot controlled by an Admittance Swarm Initialized Adaptive (ASIA). The aim of this paper was to develop a robust adaptive controller integrated with admittance model to overcome human–robot interaction forces generated by the wearer. The parameters of the ASIA controller were efficiently initialized using swarm beetle antenna searching. An experiment was conducted on a prototype lower limb exoskeleton with four degrees of freedom, involving a healthy human subject for gait trajectory analysis. The results demonstrated the effectiveness of the proposed method in terms of control performance, steady-state error reduction, and robustness. The statistical analysis revealed that the ASIA performed 63 %, 53 % and 48 % less in average error compared to adaptive conventional controllers used in the same exoskeleton platform. The findings ascertained the potential of the ASIA controller in improving human mobility through lower limb exoskeleton applications.