Teaches a robotic lower-limb exoskeleton to recognise how its wearer is walking (on level ground, up or down ramps, up or down stairs) without collecting large amounts of training data from each new user. The work proposes an Adaptive Fuzzy-Based Algorithm and demonstrates an adaptive neuro-fuzzy inference system (ANFIS) for better walking assistance.
Natee Chirachongcharoen
M.Eng. 2024; after graduating, joined Fibio Robotics as a Robotics Engineer
All lab members →Publications
1
N. Chirachongcharoen, S. Nisar
Artificial Life and Robotics, vol. 29, no. 1, pp. 389–397
2
N. Chirachongcharoen, S. Nisar
42nd Annual Conf. of the Robotics Society of Japan (RSJ) 2024
3
Human Gait-Type Recognition without Pre-Training Using Adaptive Machine Learning for Lower-Limb Exoskeleton Thesis
N. Chirachongcharoen
Master's thesis, Kyoto University of Advanced Science, Kyoto, Japan · Advisor: S. Nisar
4
N. Chirachongcharoen, S. Nisar
28th Int. Symposium on Artificial Life and Robotics (AROB) 2023
