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Review of Vision-Based Environmental Perception for Lower-Limb Exoskeleton Robots.
Wang, Chen; Pei, Zhongcai; Fan, Yanan; Qiu, Shuang; Tang, Zhiyong.
Afiliação
  • Wang C; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
  • Pei Z; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
  • Fan Y; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
  • Qiu S; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
  • Tang Z; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
Biomimetics (Basel) ; 9(4)2024 Apr 22.
Article em En | MEDLINE | ID: mdl-38667265
ABSTRACT
The exoskeleton robot is a wearable electromechanical device inspired by animal exoskeletons. It combines technologies such as sensing, control, information, and mobile computing, enhancing human physical abilities and assisting in rehabilitation training. In recent years, with the development of visual sensors and deep learning, the environmental perception of exoskeletons has drawn widespread attention in the industry. Environmental perception can provide exoskeletons with a certain level of autonomous perception and decision-making ability, enhance their stability and safety in complex environments, and improve the human-machine-environment interaction loop. This paper provides a review of environmental perception and its related technologies of lower-limb exoskeleton robots. First, we briefly introduce the visual sensors and control system. Second, we analyze and summarize the key technologies of environmental perception, including related datasets, detection of critical terrains, and environment-oriented adaptive gait planning. Finally, we analyze the current factors limiting the development of exoskeleton environmental perception and propose future directions.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Biomimetics (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Biomimetics (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China