Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/9022
Title: Portable brainwave controlled robotic dog for therapy
Authors: Lau, Chi-Yat 
Dr. YUEN Man-Ching, Connie 
Yung, Chi-Wai 
Liang, JiaJie 
Mak, Wing Chi 
Chan, Ho Yeung 
Ha, Fong Yu 
Ng, Zheng Tan 
Wong, Hong San 
Issue Date: 2023
Publisher: IOS Press
Source: Lau, Chi Yai, Yuen, Man Ching, Yung, Chi Wai, Liang, JiaJie, Mak, Wing Chi, Chan, Ho Yeung, Ha, Fong Yu, Ng, Zheng Tan & Wong, Hong San (2023). Portable brainwave controlled robotic dog for therapy. In Tallón-Ballesteros, A.J. & Beltrán-Barba, R. (Eds.). Fuzzy systems and data mining IX : Proceedings of FSDM 2023. FSDM 2023, Chongqing, China (pp. 833-842). IOS Press.
Conference: The 9th International Conference on Fuzzy Systems and Data Mining 
Abstract: With the revolution of technology, robots are an inevitable trend as robots can do what humans do more efficiently and at a lower cost. However, humans have retained labor force dominance because robots have suffered from immature software and hardware. To solve the problem of immatureness, we exploit a platform that can integrate the systems of multi-robots and strives to let all the users control their own robots through the platform. Our goal is to develop a ROS (Robot Operating System) package that can incorporate a small robot dog which allows the robot dog to respond to our industrial partner, R2C2, webapp commands and in addition to using brain waves to control the walking path. Our platform provides an intuitive and accessible interface for users to control the robot’s movements and behavior, increasing the robot’ s versatility and usage for applications such as therapy, entertainment, education, and research. Overall, our project represents an exciting step forward in the field of robotics, and we are excited to continue exploring new ways to improve the interaction between humans and machines.
Type: Conference Paper
URI: http://hdl.handle.net/20.500.11861/9022
ISBN: 9781643684703
9781643684710
DOI: 10.3233/FAIA231095
Appears in Collections:Applied Data Science - Publication

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