Alwan Abdul Zaki, E. Mulyana, Rina Mardiati, Ulfiah
{"title":"基于模糊逻辑控制的墙体跟踪机器人运动建模","authors":"Alwan Abdul Zaki, E. Mulyana, Rina Mardiati, Ulfiah","doi":"10.1109/ICWT50448.2020.9243624","DOIUrl":null,"url":null,"abstract":"In this modern times, robot technology is rapidly having a great progress day by day, especially in robot wall tracer. Robot wall tracer was very useful to lighten human jobs in industry, manufacturing, and infrastructure. Some problems that arises in building the wall tracer robot is how to make a navigation system on the robot so that it always remains in the set point position. Previous study has been done to solve this problem using various methods and approaches such as implemented some intelligence program that used to navigate the robot wall tracer. In this study, we try to design and build a robot wall tracer using an Arduino MEGA microcontroller as the brain for control robot and the HC-SR04 ultrasonic sensor based on fuzzy logic to control the position and DC motor speed. In this study, testing was carried out in terms of hardware and software, as well as overall system testing. Based on hardware testing obtained PWM left motor 110 and PWM right motor 107. Meanwhile, for software testing, it is found that the fuzzy logic has been successfully implemented in the robot. The results of the calculation of fuzzy logic on the robot are compared with the calculation of simulation results and manual calculations. In addition, a performance comparison test of the robot system was conducted, and it was found that robots equipped with fuzzy logic were 2.3 seconds faster than robots without fuzzy logic.","PeriodicalId":304605,"journal":{"name":"2020 6th International Conference on Wireless and Telematics (ICWT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Modeling Wall Tracer Robot Motion Based on Fuzzy Logic Control\",\"authors\":\"Alwan Abdul Zaki, E. Mulyana, Rina Mardiati, Ulfiah\",\"doi\":\"10.1109/ICWT50448.2020.9243624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this modern times, robot technology is rapidly having a great progress day by day, especially in robot wall tracer. Robot wall tracer was very useful to lighten human jobs in industry, manufacturing, and infrastructure. Some problems that arises in building the wall tracer robot is how to make a navigation system on the robot so that it always remains in the set point position. Previous study has been done to solve this problem using various methods and approaches such as implemented some intelligence program that used to navigate the robot wall tracer. In this study, we try to design and build a robot wall tracer using an Arduino MEGA microcontroller as the brain for control robot and the HC-SR04 ultrasonic sensor based on fuzzy logic to control the position and DC motor speed. In this study, testing was carried out in terms of hardware and software, as well as overall system testing. Based on hardware testing obtained PWM left motor 110 and PWM right motor 107. Meanwhile, for software testing, it is found that the fuzzy logic has been successfully implemented in the robot. The results of the calculation of fuzzy logic on the robot are compared with the calculation of simulation results and manual calculations. In addition, a performance comparison test of the robot system was conducted, and it was found that robots equipped with fuzzy logic were 2.3 seconds faster than robots without fuzzy logic.\",\"PeriodicalId\":304605,\"journal\":{\"name\":\"2020 6th International Conference on Wireless and Telematics (ICWT)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 6th International Conference on Wireless and Telematics (ICWT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWT50448.2020.9243624\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Wireless and Telematics (ICWT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWT50448.2020.9243624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling Wall Tracer Robot Motion Based on Fuzzy Logic Control
In this modern times, robot technology is rapidly having a great progress day by day, especially in robot wall tracer. Robot wall tracer was very useful to lighten human jobs in industry, manufacturing, and infrastructure. Some problems that arises in building the wall tracer robot is how to make a navigation system on the robot so that it always remains in the set point position. Previous study has been done to solve this problem using various methods and approaches such as implemented some intelligence program that used to navigate the robot wall tracer. In this study, we try to design and build a robot wall tracer using an Arduino MEGA microcontroller as the brain for control robot and the HC-SR04 ultrasonic sensor based on fuzzy logic to control the position and DC motor speed. In this study, testing was carried out in terms of hardware and software, as well as overall system testing. Based on hardware testing obtained PWM left motor 110 and PWM right motor 107. Meanwhile, for software testing, it is found that the fuzzy logic has been successfully implemented in the robot. The results of the calculation of fuzzy logic on the robot are compared with the calculation of simulation results and manual calculations. In addition, a performance comparison test of the robot system was conducted, and it was found that robots equipped with fuzzy logic were 2.3 seconds faster than robots without fuzzy logic.