S. Kautsar, B. Widiawan, B. Etikasari, Saiful Anwar, Rosiana Dwi Yunita, M. Syai’in
{"title":"基于深度相机的差动轮式人跟随机器人简单控制算法","authors":"S. Kautsar, B. Widiawan, B. Etikasari, Saiful Anwar, Rosiana Dwi Yunita, M. Syai’in","doi":"10.1109/ICOMITEE.2019.8921165","DOIUrl":null,"url":null,"abstract":"Industrial Revolution 4.0 is the center of automatic technology development and adoption. This applies to the development of industrial automation and information technology. In the manufacturing industry, machines have been able to work autonomously to carry out the production process quickly and precisely. Even in the development of information technology, expert systems have been embedded in various smart phones. There are many things that can be controlled through smart phones that are connected to the internet network. Not only in manufacturing industries or offices, the development of industrial technology 4.0 has also begun to be implemented in homes. Automatic robotic cleaning technology, or smart home applications can be used commercially. In fact, using people tracking technology, automatic trolleys have been applied to help consumers in supermarkets. In this paper, person-following robot was developed. We use depth cameras to recognize human movement. 3D data is used as a reference value in a human follower system. Minimizing computing time, the dynamic decision tree method is used. This offers lighter and faster computational processing than using the fuzzy or NN method. Based on the testing result, a good robot performance is obtained. Robots can follow human movements in real-time on various testing paths.","PeriodicalId":137739,"journal":{"name":"2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Simple Algorithm for Person-Following Robot Control with Differential Wheeled based on Depth Camera\",\"authors\":\"S. Kautsar, B. Widiawan, B. Etikasari, Saiful Anwar, Rosiana Dwi Yunita, M. Syai’in\",\"doi\":\"10.1109/ICOMITEE.2019.8921165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Industrial Revolution 4.0 is the center of automatic technology development and adoption. This applies to the development of industrial automation and information technology. In the manufacturing industry, machines have been able to work autonomously to carry out the production process quickly and precisely. Even in the development of information technology, expert systems have been embedded in various smart phones. There are many things that can be controlled through smart phones that are connected to the internet network. Not only in manufacturing industries or offices, the development of industrial technology 4.0 has also begun to be implemented in homes. Automatic robotic cleaning technology, or smart home applications can be used commercially. In fact, using people tracking technology, automatic trolleys have been applied to help consumers in supermarkets. In this paper, person-following robot was developed. We use depth cameras to recognize human movement. 3D data is used as a reference value in a human follower system. Minimizing computing time, the dynamic decision tree method is used. This offers lighter and faster computational processing than using the fuzzy or NN method. Based on the testing result, a good robot performance is obtained. Robots can follow human movements in real-time on various testing paths.\",\"PeriodicalId\":137739,\"journal\":{\"name\":\"2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOMITEE.2019.8921165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOMITEE.2019.8921165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Simple Algorithm for Person-Following Robot Control with Differential Wheeled based on Depth Camera
Industrial Revolution 4.0 is the center of automatic technology development and adoption. This applies to the development of industrial automation and information technology. In the manufacturing industry, machines have been able to work autonomously to carry out the production process quickly and precisely. Even in the development of information technology, expert systems have been embedded in various smart phones. There are many things that can be controlled through smart phones that are connected to the internet network. Not only in manufacturing industries or offices, the development of industrial technology 4.0 has also begun to be implemented in homes. Automatic robotic cleaning technology, or smart home applications can be used commercially. In fact, using people tracking technology, automatic trolleys have been applied to help consumers in supermarkets. In this paper, person-following robot was developed. We use depth cameras to recognize human movement. 3D data is used as a reference value in a human follower system. Minimizing computing time, the dynamic decision tree method is used. This offers lighter and faster computational processing than using the fuzzy or NN method. Based on the testing result, a good robot performance is obtained. Robots can follow human movements in real-time on various testing paths.