From sensing to control of lower limb exoskeleton: a systematic review. (2022)

• Record Type: Journal Article
• Authors: Sun, Yuanxi; Tang, Yuntao; Zheng, Jia; Dong, Dianbiao; Chen, Xiaohong; Bai, Long
• Is Part Of: Annual reviews in control. Volume 53(2022)
• Page Start: 83
• Page End: 96
• Publication Date: 2022
• Subjects: Exoskeleton -- Control -- Sensor -- Robotics -- Lower extremity; Automatic control -- Periodicals; Periodicals; 629.805
• DOI: 10.1016/j.arcontrol.2022.04.003
• Languages: English
• ISSNs: 1367-5788

Abstract

Highlight: Systematical introduction of lower limb exoskeleton's development and control Detailed elaboration of lower limb exoskeleton's perception approaches In-depth investigation of lower limb exoskeleton's control methods Quantitative and qualitative summary of lower limb exoskeleton's control Discussion of exoskeleton control challenges and possible research directions Abstract: As a typical application of the human-computer interaction device, the lower limb exoskeleton has attracted many researchers' attention in recent years in an attempt to improve its functionality in human body assistance, augmentation, treatment, and protection. Essentially, the interaction between the lower limb exoskeleton and the subject is mainly realized through its sensing and control system. The sensing and control of lower limb exoskeletons will significantly affect the subject's actual wearing effect in lower extremity assistance or enhancement. However, due to the limitations of sensing and control techniques, the lower limb exoskeleton is still challenging to achieve a large-scale popularization and application. Therefore, this paper investigated the literature regarding the sensing and control of lower limb exoskeletons in recent years and studied the influences of different sensor signals and controller modeling on the exoskeleton performance. In addition, the current research challenges of insufficient stability and comfort in lower limb exoskeleton control are discussed, and possible innovative insights of functional material-based actuation, invasive and epidermal electronic sensing, and data-driven deep learning are analyzed in-depth. Some future research directions of the exoskeleton control are also provided to facilitate the further development of the exoskeleton control.