Development of autonomous robot using fuzzy inference system (FIS) for indoor ultraviolet (UV) disinfection
In the situation of the coronavirus disease (COVID-19) pandemic, a solution to disinfect public rooms in a faster and more effective way is needed. This paper presents a design of an autonomous robot that can avoid obstacles in an unknown environment using a Fuzzy inference system (FIS) as the initi...
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| creator | Simarmata, Adven Dewi, Tiara Kusuma Fikri, Muhamad Rausyan Saptaji, Kushendarsyah |
| description | In the situation of the coronavirus disease (COVID-19) pandemic, a solution to disinfect public rooms in a faster and more effective way is needed. This paper presents a design of an autonomous robot that can avoid obstacles in an unknown environment using a Fuzzy inference system (FIS) as the initial step to develop autonomous UV disinfection robot. The advantage of using a Fuzzy inference system for the obstacle avoidance algorithm in the robot is the more effective respond in avoiding static and dynamic obstacles. The Fuzzy inference system enables the robot to vary the speed of the right and left wheels depending on the distance of obstacles at the front, left, and right. Therefore, the robot could vary both the degrees and speed when it turns away from the obstacles according to the rule base made. Hence, implementing FIS in the obstacle avoidance algorithm can increase the effectiveness of the robot in avoiding obstacles, thus make the robot reach the target faster. The experimental result shows that the robot prototype can avoid the obstacles at the front, left, and right, with various turning angle and speed depending on the distance of obstacles. |
| doi_str_mv | 10.1063/5.0112788 |
| format | Conference Proceeding |
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This paper presents a design of an autonomous robot that can avoid obstacles in an unknown environment using a Fuzzy inference system (FIS) as the initial step to develop autonomous UV disinfection robot. The advantage of using a Fuzzy inference system for the obstacle avoidance algorithm in the robot is the more effective respond in avoiding static and dynamic obstacles. The Fuzzy inference system enables the robot to vary the speed of the right and left wheels depending on the distance of obstacles at the front, left, and right. Therefore, the robot could vary both the degrees and speed when it turns away from the obstacles according to the rule base made. Hence, implementing FIS in the obstacle avoidance algorithm can increase the effectiveness of the robot in avoiding obstacles, thus make the robot reach the target faster. 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The experimental result shows that the robot prototype can avoid the obstacles at the front, left, and right, with various turning angle and speed depending on the distance of obstacles.</description><subject>Algorithms</subject><subject>Coronaviruses</subject><subject>Disinfection</subject><subject>Inference</subject><subject>Obstacle avoidance</subject><subject>Robots</subject><subject>Unknown environments</subject><subject>Viral diseases</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kEtLw0AUhQdRsFYX_oMBN62QOpPJPLKUalUouNCKuyGZh6QmmTgzKbS_3pQW3Lk6i_ude-85AFxjNMOIkTs6QxinXIgTMMKU4oQzzE7BCKE8S9KMfJ6DixDWCKU552IEvh_MxtSua0wbobOw6KNrXeP6AL0rXYR9qNovaPvdbgur1hpvWmVg2IZoGjhZvLxNoXV-GGk3SF9HX2wqV5sIJ6uPKdRV2LtUrFx7Cc5sUQdzddQxWC0e3-fPyfL16WV-v0w6zERMiKKaFphkGmdc5YhzrUyGhUYlYyUVQzhMsaC2yNOUKKOIGdJprfLcljxVZAxuDns77356E6Jcu963w0mZCsQYRoShgbo9UEFVsdj_JztfNYXfyo3zkspjkbLT9j8YI7lv_s9AfgFTT3YK</recordid><startdate>20230427</startdate><enddate>20230427</enddate><creator>Simarmata, Adven</creator><creator>Dewi, Tiara Kusuma</creator><creator>Fikri, Muhamad Rausyan</creator><creator>Saptaji, Kushendarsyah</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230427</creationdate><title>Development of autonomous robot using fuzzy inference system (FIS) for indoor ultraviolet (UV) disinfection</title><author>Simarmata, Adven ; Dewi, Tiara Kusuma ; Fikri, Muhamad Rausyan ; Saptaji, Kushendarsyah</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p168t-3c5d5a134d147c9077dce418d0b66b5878815185fa9223cec3e009ddc99fb72c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Coronaviruses</topic><topic>Disinfection</topic><topic>Inference</topic><topic>Obstacle avoidance</topic><topic>Robots</topic><topic>Unknown environments</topic><topic>Viral diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Simarmata, Adven</creatorcontrib><creatorcontrib>Dewi, Tiara Kusuma</creatorcontrib><creatorcontrib>Fikri, Muhamad Rausyan</creatorcontrib><creatorcontrib>Saptaji, Kushendarsyah</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Simarmata, Adven</au><au>Dewi, Tiara Kusuma</au><au>Fikri, Muhamad Rausyan</au><au>Saptaji, Kushendarsyah</au><au>Helios, Muhammad Penta</au><au>Aji, Sudi Dul</au><au>Triawan, Farid</au><au>Miharja, Deni</au><au>Rinanti, Astri</au><au>Abdullah, Ade Gafar</au><au>Rohadi, Erfan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Development of autonomous robot using fuzzy inference system (FIS) for indoor ultraviolet (UV) disinfection</atitle><btitle>AIP conference proceedings</btitle><date>2023-04-27</date><risdate>2023</risdate><volume>2646</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>In the situation of the coronavirus disease (COVID-19) pandemic, a solution to disinfect public rooms in a faster and more effective way is needed. This paper presents a design of an autonomous robot that can avoid obstacles in an unknown environment using a Fuzzy inference system (FIS) as the initial step to develop autonomous UV disinfection robot. The advantage of using a Fuzzy inference system for the obstacle avoidance algorithm in the robot is the more effective respond in avoiding static and dynamic obstacles. The Fuzzy inference system enables the robot to vary the speed of the right and left wheels depending on the distance of obstacles at the front, left, and right. Therefore, the robot could vary both the degrees and speed when it turns away from the obstacles according to the rule base made. Hence, implementing FIS in the obstacle avoidance algorithm can increase the effectiveness of the robot in avoiding obstacles, thus make the robot reach the target faster. 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| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP conference proceedings, 2023, Vol.2646 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
| recordid | cdi_scitation_primary_10_1063_5_0112788 |
| source | AIP Journals Complete |
| subjects | Algorithms Coronaviruses Disinfection Inference Obstacle avoidance Robots Unknown environments Viral diseases |
| title | Development of autonomous robot using fuzzy inference system (FIS) for indoor ultraviolet (UV) disinfection |
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