Oğulcan Işıtman, Hakan Kandemir, G. Alcan, Zoran M Cenev, Quan Zhou
{"title":"Simultaneous and Independent Micromanipulation of Two Identical Particles with Robotic Electromagnetic Needles","authors":"Oğulcan Işıtman, Hakan Kandemir, G. Alcan, Zoran M Cenev, Quan Zhou","doi":"10.1109/MARSS55884.2022.9870468","DOIUrl":null,"url":null,"abstract":"Magnetic manipulation of particles at close vicinity is a challenging task. In this paper, we propose simultaneous and independent manipulation of two identical particles at close vicinity using two mobile robotic electromagnetic needles. We developed a neural network that can predict the magnetic flux density gradient for any given needle positions. Using the neural network, we developed a control algorithm to solve the optimal needle positions that generate the forces in the required directions while keeping a safe distance between the two needles and particles. We applied our method in five typical cases of simultaneous and independent microparticle manipulation, with the closest particle separation of 30 μm.","PeriodicalId":144730,"journal":{"name":"2022 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MARSS55884.2022.9870468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Magnetic manipulation of particles at close vicinity is a challenging task. In this paper, we propose simultaneous and independent manipulation of two identical particles at close vicinity using two mobile robotic electromagnetic needles. We developed a neural network that can predict the magnetic flux density gradient for any given needle positions. Using the neural network, we developed a control algorithm to solve the optimal needle positions that generate the forces in the required directions while keeping a safe distance between the two needles and particles. We applied our method in five typical cases of simultaneous and independent microparticle manipulation, with the closest particle separation of 30 μm.