In this study, a novel method for designing real-time motion profiles based on a weighted fuzzy logic algorithm for an exoskeleton robot was proposed. When developing exoskeleton robots, it is important that they can identify a wearer's motion intent in real time; therefore, we produced the motion profiles of an exoskeleton robot knee joint angles using hip joint angles and plantar pressure sensors. Two types of sensors were used to design the robot's knee estimation angle profiles in real time-namely, hip joint angles to design the fuzzy logic algorithm and plantar pressure sensors to classify the robot's gait phase. In the fuzzy set, four fuzzy inputs were produced through the hip joint angles; then, four fuzzy outputs were implemented based on the fuzzy inputs using 68 predefined rule bases in the fuzzy inference. The fuzzy outputs were used as the basis for calculating the motion profiles during the defuzzification. To adjust the knee angle of the robot, the weighted values were assigned to each hip joint angle section. To validate the proposed algorithm, we conducted two experiments-namely, the exoskeleton robot with and without an actuator. The method was verified through experiments showing that the motion profiles estimated the robot's knee angles close to the desired angles.
Bibliographical noteFunding Information:
This research was supported by the Basic Science Research Program grant funded by the National Research Foundation of Korea (NRF) (No. 2017R1A2B4009265).
© 2020 by the authors.
All Science Journal Classification (ASJC) codes
- Materials Science(all)
- Process Chemistry and Technology
- Computer Science Applications
- Fluid Flow and Transfer Processes