https://oldena.lpnu.ua/handle/ntb/52488| Title: | MEMS-based Inertial Sensor Signals and Machine Learning Methods for Classifying Robot Motion |
| Authors: | Ponomaryova, Ganna Nevlydov, Igor Filipenko, Oleksandr Volkova, Mariya |
| Affiliation: | Kharkiv National University of Radio Electronics |
| Bibliographic description (Ukraine): | MEMS-based Inertial Sensor Signals and Machine Learning Methods for Classifying Robot Motion / Ganna Ponomaryova, Igor Nevlydov, Oleksandr Filipenko, Mariya Volkova // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 13–16. — (Big Data & Data Science Using Intelligent Approaches). |
| Bibliographic description (International): | MEMS-based Inertial Sensor Signals and Machine Learning Methods for Classifying Robot Motion / Ganna Ponomaryova, Igor Nevlydov, Oleksandr Filipenko, Mariya Volkova // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 13–16. — (Big Data & Data Science Using Intelligent Approaches). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | robot MEMS classification control |
| Number of pages: | 4 |
| Page range: | 13-16 |
| Start page: | 13 |
| End page: | 16 |
| Abstract: | Robot state classification using machine-learning methods and MEMS sensors data is proposed in the paper. An experiment was performed with a three-axis MEMS gyroscope rigidly fixed to the robot body. In it we investigated the possibilities of various machine-learning methods for solving classification task. |
| URI: | https://ena.lpnu.ua/handle/ntb/52488 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | https://www.invensense.com/wp-content/uploads/2015/02/PS-MPU9250A-01- https://ieeexplore.ieee.org/document/5285608// https://pdfs.semanticscholar.org/89ca/d05d53302b4b8c465f3fc9b9eec924aff567.pdf?_ga=2.160054457.507168460.1529006792-191559443.1528161624/ https://doi.org/10.1023/A:1022627411411 http://wwwstat.stanford.edu/ |
| References (Ukraine): | [1] F. Coito, A. Eleutério, S. Valtchev, and F. Coito, “Tracking a Mobile Robot Position Using Vision and Inertial Sensor,” 5th IFIP WG 5.5/SOCOLNET DoCEIS 2014, Costa de Caparica, Portugal, AICT423, Springer, pp. 201-20, April 7-9, 2014. [2] Inven Sense. MPU-9250 Product Specification, Revision 1.1, InvenSense Inc. [ONLINE] Available at: https://www.invensense.com/wp-content/uploads/2015/02/PS-MPU9250A-01- v1.1.pdf. [Accessed 26/12/2017]. [3] K. Noda, Y. Hashimoto, Y. Tanaka, and Ichiro Shimoyama, “MEMS on robot applications,” TRANSDUCERS 2009 International SolidState Sensors, Actuators and Microsystems Conference [ONLINE] Available at: https://ieeexplore.ieee.org/document/5285608// [4] K. Frank, J. Vera Nadales, P. Robertson, and M. Angermann, “Reliable Real-Time Recognition of Motion Related Human Activities Using MEMS Inertial Sensors,” [ONLINE] Available at: https://pdfs.semanticscholar.org/89ca/d05d53302b4b8c465f3fc9b9eec924aff567.pdf?_ga=2.160054457.507168460.1529006792-191559443.1528161624/ [5] S. B. Kotsiantis, “Supervised machine learning: A review of classification techniques,” Informatica, vol. 31, pp. 249–268, 2007. [6] C. Cortes, and V. Vapnik, “Support-vector network,” Machine Learning, vol. 20, issue 3, pp. 273-297, Sept. 1995. [Online]. Available: https://doi.org/10.1023/A:1022627411411. [7] J. Zhu, S. Rosset, H. Zou, and T. Hastie, “Multiclass AdaBoost,” Technical report, Stanford Univ, 2005. Available at http://wwwstat.stanford.edu/ hastie/Papers/ samme.pdf. [8] Y. Freund, and R. E. Schapire, “Experiments with a New Boosting Algorithm,” in L.Saitta, ed., ‘Proceedings of the Thirteenth International Conference on Machine Learning (ICML’96)’, Morgan Kaufmann,1995, pp. 148–156. [9] E. Gatnar, “Fusion of Multiple Statistical Classifiers”, in C. Preisach, H. Burkhardt, L. Schmidt-Thieme and R. Decker, eds, “Data Analysis, Machine Learning and Applications,” Studies in Classification, Data Analysis, and Knowledge Organization, Springer, Berlin/Heidelberg, 2008, pp. 19–27. |
| References (International): | [1] F. Coito, A. Eleutério, S. Valtchev, and F. Coito, "Tracking a Mobile Robot Position Using Vision and Inertial Sensor," 5th IFIP WG 5.5/SOCOLNET DoCEIS 2014, Costa de Caparica, Portugal, AICT423, Springer, pp. 201-20, April 7-9, 2014. [2] Inven Sense. MPU-9250 Product Specification, Revision 1.1, InvenSense Inc. [ONLINE] Available at: https://www.invensense.com/wp-content/uploads/2015/02/PS-MPU9250A-01- v1.1.pdf. [Accessed 26/12/2017]. [3] K. Noda, Y. Hashimoto, Y. Tanaka, and Ichiro Shimoyama, "MEMS on robot applications," TRANSDUCERS 2009 International SolidState Sensors, Actuators and Microsystems Conference [ONLINE] Available at: https://ieeexplore.ieee.org/document/5285608// [4] K. Frank, J. Vera Nadales, P. Robertson, and M. Angermann, "Reliable Real-Time Recognition of Motion Related Human Activities Using MEMS Inertial Sensors," [ONLINE] Available at: https://pdfs.semanticscholar.org/89ca/d05d53302b4b8c465f3fc9b9eec924aff567.pdf?_ga=2.160054457.507168460.1529006792-191559443.1528161624/ [5] S. B. Kotsiantis, "Supervised machine learning: A review of classification techniques," Informatica, vol. 31, pp. 249–268, 2007. [6] C. Cortes, and V. Vapnik, "Support-vector network," Machine Learning, vol. 20, issue 3, pp. 273-297, Sept. 1995. [Online]. Available: https://doi.org/10.1023/A:1022627411411. [7] J. Zhu, S. Rosset, H. Zou, and T. Hastie, "Multiclass AdaBoost," Technical report, Stanford Univ, 2005. Available at http://wwwstat.stanford.edu/ hastie/Papers/ samme.pdf. [8] Y. Freund, and R. E. Schapire, "Experiments with a New Boosting Algorithm," in L.Saitta, ed., ‘Proceedings of the Thirteenth International Conference on Machine Learning (ICML’96)’, Morgan Kaufmann,1995, pp. 148–156. [9] E. Gatnar, "Fusion of Multiple Statistical Classifiers", in C. Preisach, H. Burkhardt, L. Schmidt-Thieme and R. Decker, eds, "Data Analysis, Machine Learning and Applications," Studies in Classification, Data Analysis, and Knowledge Organization, Springer, Berlin/Heidelberg, 2008, pp. 19–27. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Ponomaryova_G-MEMS_based_Inertial_Sensor_13-16.pdf | 269.31 kB | Adobe PDF | View/Open | |
| 2018_Ponomaryova_G-MEMS_based_Inertial_Sensor_13-16__COVER.png | 1.61 MB | image/png | View/Open |
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