TY - JOUR
T1 - Olfactory arm mobile robot for object inspection based on fuzzy logic and support vector machine
AU - Rendyansyah,
AU - Rivai, Muhammad
AU - Purwanto, Djoko
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2019/4/16
Y1 - 2019/4/16
N2 - In recent years, there have been suspicious objects containing chemical materials intentionally placed on roads, fields and parking lots. The objects are considered harmful to be examined. Therefore, we need tools that can replace people in checking the dangerous objects. Robot is considered as a technology that can be applied to handle it. This study has designed a mobile robot system equipped with robotic arm and electronic nose to inspect the suspected object. The robotic arm is used to bring the electronic nose closer to the object's surface. This robot can find the source of gas and surround the object with a distance of 20 cm. The movement of the mobile robot and robotic arm is controlled using fuzzy logic. The Support Vector Machine method is used to identify gas types. This olfactory arm mobile robot can find a gas source and recognize the type of gas with a success rate of 92%.
AB - In recent years, there have been suspicious objects containing chemical materials intentionally placed on roads, fields and parking lots. The objects are considered harmful to be examined. Therefore, we need tools that can replace people in checking the dangerous objects. Robot is considered as a technology that can be applied to handle it. This study has designed a mobile robot system equipped with robotic arm and electronic nose to inspect the suspected object. The robotic arm is used to bring the electronic nose closer to the object's surface. This robot can find the source of gas and surround the object with a distance of 20 cm. The movement of the mobile robot and robotic arm is controlled using fuzzy logic. The Support Vector Machine method is used to identify gas types. This olfactory arm mobile robot can find a gas source and recognize the type of gas with a success rate of 92%.
UR - http://www.scopus.com/inward/record.url?scp=85065702678&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1196/1/012019
DO - 10.1088/1742-6596/1196/1/012019
M3 - Conference article
AN - SCOPUS:85065702678
SN - 1742-6588
VL - 1196
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 12019
T2 - International Conference on Information System, Computer Science and Engineering 2018, ICONISCSE 2018
Y2 - 26 November 2018 through 27 November 2018
ER -