A Novel Method for Designing Motion Profiles Based on a Fuzzy Logic Algorithm Using the Hip Joint Angles of a Lower-Limb Exoskeleton Robot
Autor: | Yoon Su Baek, Buchun Song, Sang Yong Park, Dongyoung Lee |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Computer science exoskeleton robot Fuzzy set ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Knee Joint lcsh:Technology Fuzzy logic Defuzzification real-time motion profiles Computer Science::Robotics lcsh:Chemistry 020901 industrial engineering & automation electro-hydraulic actuator (EHA) General Materials Science Computer vision lcsh:QH301-705.5 Instrumentation Fluid Flow and Transfer Processes Basis (linear algebra) lcsh:T business.industry Process Chemistry and Technology General Engineering 021001 nanoscience & nanotechnology lcsh:QC1-999 Computer Science Applications Exoskeleton lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 Robot Artificial intelligence weighted fuzzy logic algorithm lcsh:Engineering (General). Civil engineering (General) 0210 nano-technology Actuator business lcsh:Physics |
Zdroj: | Applied Sciences Volume 10 Issue 19 Applied Sciences, Vol 10, Iss 6852, p 6852 (2020) |
ISSN: | 2076-3417 |
DOI: | 10.3390/app10196852 |
Popis: | 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&rsquo 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&rsquo s knee estimation angle profiles in real time&mdash namely, hip joint angles to design the fuzzy logic algorithm and plantar pressure sensors to classify the robot&rsquo 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&mdash namely, the exoskeleton robot with and without an actuator. The method was verified through experiments showing that the motion profiles estimated the robot&rsquo s knee angles close to the desired angles. |
Databáze: | OpenAIRE |
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