Learning-based motion-intention prediction for end-point control of upper-limb-assistive robots

• Main Authors: Yang, Sibo, Garg, Neha P., Gao, Ruobin, Yuan, Meng, Noronha, Bernardo, Ang, Wei Tech, Accoto, Dino
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Mechanical engineering; Engineering::Computer science and engineering; Upper Limb Assistive Robots; Wearable Sensors
• Online Access: https://hdl.handle.net/10356/169537
• Institution: Nanyang Technological University

The lack of intuitive and active human-robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing syst...