BBAuthors: Huang, H.; Advisor: -; Participants: Lin, J.; Wu, L.; Fang, B.; Wen, Z.; Sun, F. (2019)
This paper focuses on multi-modal Information Perception (IP) for Soft Robotic Hands (SRHs) using
Machine Learning (ML) algorithms. A flexible Optical Fiber-based Curvature Sensor (OFCS) is fabricated,
consisting of a Light-Emitting Diode (LED), photosensitive detector, and optical fiber. Bending the roughened optical fiber generates lower light intensity, which reflecting the curvature of the soft finger. Together with the curvature and pressure information, multi-modal IP is performed to improve the recognition accuracy. Recognitions of gesture, object shape, size, and weight are implemented with multiple ML approaches, including the Supervised Learning Algorithms (SLAs) of K-Nearest N... 
