RESEARCH OF ROBOTIC SYSTEMS CONTROL METHODS USING MOTION RECOGNITION TOOLS, MACHINE LEARNING AND SKELETALIZATION ALGORITHMS
DOI:
https://doi.org/10.17770/sie2021vol5.6451Keywords:
machine learning, motion recognition, robotic system, skeletalization algorithmsAbstract
The aim of the research is to develop possible control methods of robotic systems based on the usability of motion detection equipment, skeletalization algorithms and robotic systems, integrating them into the existing test bench by performing compatibility tests. The article reviews the possible motion detection systems, establishing the criteria of applicability in the control of robotic systems, describes the experimental research plan, research stand, discusses the research results and presents summarized conclusions and suggestions for the integration of research results into the educational process.
References
Carmelo, M., Acutis, A., Carrabba, M., Criscenti, G., Vozzi, G. (2016). Machine design for multimaterial processing. Nanobiomaterials in Soft Tissue Engineering: Applications of Nanobiomaterials, Volume 5, 111-140. DOI: https://doi.org/10.1016/B978-0-323-42865-1.00005-2
Chaminade, T., & Cheng, G. (2019). Social cognitive neuroscience and humanoid robotics. Journal of Physiology – Paris, Volume 103, 286-295. DOI: https://doi.org/10.1016/j.jphysparis.2009.08.011
Davies, E.R. (2017). Computer Vision. London: AcademicPress.
Jin, D., Chen, C., Hoffman, E.A., Saha, P.K. (2017) Curve skeletonization using minimum-cost path. Skeletonization: Theory, Methods and Applications, 151-180. DOI: https://doi.org/10.1016/B978-0-08-101291-8.00007-9
Kar, A. (2011). Skeletal Tracking using Microsoft Kinect. Kanpur.
Nava, A., Brena, R., Garrido, L. (2014). Recognizing Activities Using a Kinect Skeleton Tracking and Hidden Markov Models. 13th Mexican International Conference on Artificial Intelligence (MICAI). DOI: 10.1109/MICAI.2014.18
Palagyi, K. (n.d.). Skeletonization. Retrieved from: http://www.inf.u-szeged.hu/~palagyi/skel/skel.html
Palionyte, A (2011). Discretization of Continuum Structures via Image Algebra Methods. Vilnius: Vilnius Gediminas Technical University.
Paulinas, M., & Rokicki, J. (2008). Panasios formos pavirsiu, centrines asies radimo ir filtravimo metodika. Biomedical Engineering, 209-212.
Rokicki, J. (2010). Skeletavimo metodu apzvalga. Science - Future of Lithuania, Vol. 2 (No. 1), 19-22.
Saha, P.K., Borgefors, G., Baja, G.S. (2017). Skeletonization and its applications – a review. Skeletonization: Theory, Methods and Applications, 3-42. DOI: https://doi.org/10.1016/B978-0-08-101291-8.00002-X
Stitilis, R. (2014). Kinect Controlled Computer Game. Siauliai: Siauliai University.
Vassilevski, Y., Olshanskii, M., Simakov, S., Kolobov A., Dailov, A. (2020). Computational hemodynamics in vascular surgery. Personalized Computational Hemodynamics: Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy, 189-215. DOI: https://doi.org/10.1016/B978-0-12-815653-7.00009-9
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