Underwater Intention Recognition using Head Motion and Throat Vibration for Supernumerary Robotic Assistance

Yuqin Guo1; Rongzheng Zhang2; Wanghongjie Qiu3; Harry Asada4; Fang Wan1; Chaoyang Song3

10.1109/CASE56687.2023.10260480

2023

IEEE International Conference on Automation Science and Engineering (CASE).

2161-8070

979-8-3503-2070-1

2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)

2023-August

1-6

26-30 Aug. 2023

Auckland, New Zealand

This study presents a multi-modal mechanism for recognizing human intentions while diving underwater, aiming to achieve natural human-robot interactions through an underwater superlimb for diving assistance. The underwater environment severely limits the divers' capabilities in intention expression, which becomes more challenging when they intend to operate tools while keeping control of body postures in 3D with the various diving suits and gears. The current literature is limited in underwater intention recognition, impeding the development of intelligent wearable systems for human-robot interactions underwater. Here, we present a novel solution to simultaneously detect head motion and throat vibrations under the water in a compact, wearable design. Experiment results show that using machine learning algorithms, we achieved high performance in integrating these two modalities to translate human intentions to robot control commands for an underwater superlimb system. This study's results paved the way for future development in underwater intention recognition and underwater human-robot interactions with supernumerary support.

Vibrations Training Technological Innovation Three-dimensional Displays Robot Control Human-robot Interaction Magnetic Heads

第一

英语

EI

20234314929225

Intelligent robots ; Learning algorithms ; Machine learning ; Man machine systems ; Wearable technology

Artificial Intelligence:723.4 ; Machine Learning:723.4.2 ; Robotics:731.5 ; Robot Applications:731.6

IEEE

1.Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing, Southern University of Science and Technology, Shenzhen, Guangdong, China
2.School of Design, Southern University of Science and Technology, Shenzhen, Guangdong, China
3.Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
4.Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

Yuqin Guo,Rongzheng Zhang,Wanghongjie Qiu,et al. Underwater Intention Recognition using Head Motion and Throat Vibration for Supernumerary Robotic Assistance[C],2023:1-6.