I. Nevliudov, Ganna Ponomaryova, V. Bortnikova, S. Maksymova, K. Kolesnyk
{"title":"MEMS加速度计六足智能控制","authors":"I. Nevliudov, Ganna Ponomaryova, V. Bortnikova, S. Maksymova, K. Kolesnyk","doi":"10.1109/MEMSTECH.2018.8365721","DOIUrl":null,"url":null,"abstract":"The paper presents the results of three-axis MEMS accelerometer practical Introduction into the hexapod control system to solve the problem of classifying its states in real time. An experiment was conducted in which machine learning various methods possibilities were studied to solve the problem of classifying the current state of a walking robot. The best results for the accuracy parameter were shown by the method Medium KNN.","PeriodicalId":179131,"journal":{"name":"2018 XIV-th International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MEMS accelerometer in hexapod intellectual control\",\"authors\":\"I. Nevliudov, Ganna Ponomaryova, V. Bortnikova, S. Maksymova, K. Kolesnyk\",\"doi\":\"10.1109/MEMSTECH.2018.8365721\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents the results of three-axis MEMS accelerometer practical Introduction into the hexapod control system to solve the problem of classifying its states in real time. An experiment was conducted in which machine learning various methods possibilities were studied to solve the problem of classifying the current state of a walking robot. The best results for the accuracy parameter were shown by the method Medium KNN.\",\"PeriodicalId\":179131,\"journal\":{\"name\":\"2018 XIV-th International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)\",\"volume\":\"106 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 XIV-th International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MEMSTECH.2018.8365721\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 XIV-th International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEMSTECH.2018.8365721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MEMS accelerometer in hexapod intellectual control
The paper presents the results of three-axis MEMS accelerometer practical Introduction into the hexapod control system to solve the problem of classifying its states in real time. An experiment was conducted in which machine learning various methods possibilities were studied to solve the problem of classifying the current state of a walking robot. The best results for the accuracy parameter were shown by the method Medium KNN.