Wireless integration to optimize environmental recognition and calculate the trajectory of a group of robots
https://doi.org/10.15514/ISPRAS-2019-31(2)-6
Abstract
Nowadays artificial intelligence and swarm robotics become wide spread and take their approach in civil tasks. The main purpose of the article is to show the influence of common knowledge about surroundings sharing in the robotic group navigation problem by implementing the data transferring within the group. Methodology provided in article reviews a set of tasks implementation of which improves the results of robotic group navigation. The main questions for the research are the problems of robotics vision, path planning, data storing and data exchange. Article describes the structure of real-time laser technical vision system as the main environment-sensing tool for robots. The vision system uses dynamic triangulation principle. Article provides examples of obtained data, distance-based methods for resolution and speed control. According to the data obtained by provided vision system were decided to use matrix-based approach for robots path planning, it inflows the tasks of surroundings discretization, and trajectory approximation. Two network structure types for data transferring are compared. Authors are proposing a methodology for dynamic network forming based on leader changing system. For the confirmation of theory were developed an application of robotic group modeling. Obtained results show that common knowledge sharing between robots in-group can significantly decrease individual trajectories length.
About the Authors
Mikhail Valerievitch Valerievitch IvanovMexico
Oleg Yurievitch Sergienko
Mexico
Head of Applied Physics Department of Engineering Institute of Baja California Autonomous University
Vera Valentinovna Tyrsa
Mexico
Lars Lindner
Mexico
Julio Cesar Rodríguez-Quiñonez
Mexico
Professor of Electronic Topics with the Engineering Faculty, Autonomous University of Baja California
Wendy Flores-Fuentes
Professor-researcher at Universidad Autónoma de Baja California, at the Faculty of Engineering
Moises Rivas-Lopez
Full Researcher with the Applied Physics Department, Engineering Institute, Baja California Autonomous University
Daniel Hernández-Balbuena
Mexico
Full Professor at the Engineering Faculty of Baja California Autonomous University, Mexico
Juan Iván Nieto Hipólito
Mexico
Full Professor of Baja California Autonomous University
References
1. B. Eskridge, E. Valle, I. Schlupp. Emergence of Leadership within a Homogeneous Group. PLoS ONE, vol. 10, № 7, 2015
2. V. Pshikhopov, M. Medvedev, A. Kolesnikov, R. Fedorenko, G. Boris. Decentralized Control of a Group of Homogeneous Vehicles in Obstructed Environment. Journal of Control Science and Engineering, 2016, 8 p.
3. O. Sergiyenko, M. Ivanov, V. Tyrsa, M. Rivas-López, D. Hernández-Balbuena, W. Flores-Fuentes, J. C. Rodríguez-Quiñonez, J. I. Nieto-Hipólito, W. Hernandez, A. Tchernykh. Data transferring model determination in robotic group. Robotics and Autonomous Systems, vol. 83, 2016, pp. 251-260.
4. O.Yu. Sergiyenko, M.V. Ivanov, V.M. Kartashov, V.V. Tyrsa, D. Hernández-Balbuena and J.I. Nieto-Hipólito. Transferring model in robotic group. In Proc. of the 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), 2016, pp. 946-952.
5. David J. Grymin, Charles B. Neas and Mazen Farhood. A hierarchical approach for primitive-based motion planning and control of autonomous vehicles. Robotics and Autonomous Systems, vol. 62, no. 2, 2014, pp. 214-228.
6. Bence Kovács, Géza Szayer, Ferenc Tajti, Mauricio Burdelis, Péter Korondi. A novel potential field method for path planning of mobile robots by adapting animal motion attributes. Robotics and Autonomous Systems, vol. 82, 2016, pp. 24-34.
7. V.A. Bobkov, Y.I. Ron'shin, A.P. Kudryashov, V.Y. Mashentsev. 3D SLAM from stereoimages. Programming and Computer Software, vol. 40, № 4, 2014, pp. 159-165.
8. V.A. Bobkov, A.P. Kudryashov, S.V. Mel'man. On the Recovery of Motion of Dynamic Objects from Stereo Images. Programming and Computer Software, vol. 44, № 3, 2018, pp. 148-158.
9. N. Kamaev, V.A. Sukhenko, D.A. Karmanov. Constructing and visualizing three-dimensional sea bottom models to test AUV machine vision systems. Programming and Computer Software, vol. 43, № 3, 2017, pp. 184-195.
10. O. Vilão, D.H. Perico, I.J. Silva, T.P.D. Homem, F. Tonidandel, R.A.C. Bianchi. A Single Camera Vision System for a Humanoid Robot. In Proc. of the Joint Conference on Robotics: SBR-LARS Robotics Symposium and Robocontrol, 2014, vol. 1, pp. 181-186.
11. N. Gryaznov и A. Lopota. Computer Vision for Mobile On-Ground Robotics. Procedia Engineering, vol. 100, 2015, pp. 1376-1380.
12. M.C. Achtelik и D. Scaramuzza.Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments. IEEE Robotics & Automation Magazine, vol. 21, № 3, 2014, pp. 26-40.
13. N.F. Pashchenko, K.S. Zipa, A.V. Ignatenko. An algorithm for the visualization of stereo images simultaneously captured with different exposures. Programming and Computer Software, vol. 43, № 4, 2017, pp. 250-257.
14. G. Alenyà Ribas, S. Foix Salmerón, C. Torras Genís.ToF cameras for active vision in robotics. Sensors and Actuators A: Physical, vol. 218, 2014, pp. 10-22.
15. A. Mikhaylichenko и A.B. Kleshchenkov. Approach to Non-Contact Measurement of Geometric Parameters of Large-Sized Objects. Programming and Computer Software, vol. 44, № 4, 2018, pp. 271-277.
16. L.C. Básaca-Preciado, O.Y. Sergiyenko, J.C. Rodríguez-Quinonez, X. García, V.V. Tyrsa, M. Rivas-Lopez, D. Hernandez-Balbuena, P. Mercorelli, M. Podrygalo, A. Gurko, I. Tabakova, O. Starostenko. Optical 3D laser measurement system for navigation of autonomous mobile robot. Optics and Lasers in Engineering, vol. 54, 2014, pp. 159-169.
17. O. Sergiyenko, W. Hernandez, V. Tyrsa, L.D. Cruz, O. Starostenko, M. Pena-Cabrera. Remote Sensor for Spatial Measurements by Using Optical Scanning. Sensors (Basel), vol. 9, № 7, 2009, pp. 5477-5492.
18. P.E. Bezier. How Renault Uses Numerical Control for Car Body Design and Tooling. Society of Automotive Engineers, Detroit, MI, USA, 1968.
19. L. Han, H. Yashiro, T. Nejad, Q. Do, S. Mita. Bezier curve based path planning for autonomous vehicle in urban environment. In Proc. of the IEEE Intelligent Vehicles Symposium, 2010, pp. 1036-1042.
20. Kuniaki Kawabata, Liang Ma, Jianru Xue, Chengwei Zhu, Nanning Zheng. A path generation for automated vehicle based on Bezier curve and via-points, Robotics and Autonomous Systems, vol. 74, № A, 2015, pp. 243-252.
21. J. Hocking, Unity in Action: Multiplatform Game Development in C# with Unity 5. Shelter Island, New York, Manning Publications, 2015, 352 p.
22. X. Garcia, O. Sergiyenko, V. Tyrsa, M. Rivas-Lopez, D. Hernandez-Balbuena, J. C. Rodriguez-Quiñonez, L. C. Basaca-Preciado, P. Mercorelli. Optimization of 3D laser scanning speed by use of combined variable step. Optics and Lasers in Engineering, vol. 54, 2014, pp. 141-151.
23. R. Vincent, B. Morisset, A. Agno, M. Eriksen, C. Ortiz. Centibots: Large-scale autonomous robotic search and rescue experiment. In Proc. of the 2nd International Joint Topical Meeting on Emergency Preparedness & Response and Robotics & Remote Systems, 2008.
24. Abduladhem A. Ali, Abdulmuttalib T. Rashid, Mattia Frasca, Luigi Fortuna. An algorithm for multi-robot collision-free navigation based on shortest distance. Robotics and Autonomous Systems, vol. 75, 2016, pp. 119-128.
25. P. Muñoz, R.-M. D. María, D.F. Barrero. Unified framework for path-planning and task-planning for autonomous robots. Robotics and Autonomous Systems, vol. 82, 2016, pp. 1-14.
26. V. Trianni, E. Tuci, C. Ampatzis, M. Dorigo. Evolutionary swarm robotics: A theoretical and methodological itinerary from individual neuro-controllers to collective behaviors. In The horizons of evolutionary robotics, Cambridge [MA], MIT Press, 2014, pp. 153–178.
Review
For citations:
Ivanov M.V., Sergienko O.Yu., Tyrsa V.V., Lindner L., Rodríguez-Quiñonez J., Flores-Fuentes W., Rivas-Lopez M., Hernández-Balbuena D., Nieto Hipólito J. Wireless integration to optimize environmental recognition and calculate the trajectory of a group of robots. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2019;31(2):67-81. (In Russ.) https://doi.org/10.15514/ISPRAS-2019-31(2)-6