The study of the polymodel complex of the motion planning system of a heterogeneous group of autonomous robots in conditions of spatial-situational uncertainty

The study of the polymodel complex of the motion planning system of a heterogeneous group of autonomous robots in conditions of spatial-situational uncertainty

Dmitrii E. Motorin *
Peter the Great Saint-Petersburg Polytechnical University (SPbPU), Postgraduate Student, 29, Politekhnicheskaya ul., Saint-Petersburg, 195251, Russia, tel.: +7(921)778-85-34, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0002-8059-1837


Received 19 September 2019

Abstract
The upper level of robot group control is a system of planning of traffic and cooperative actions while solving global tasks. The main parts of such systems are a realistic presentation of the environment and ability to plan trajectories. The aim of this work is to create and study a model that allows you to generate realistic environments with given parameters and plan the movement of a robot group in them. The unit for generating discrete media, fractal surfaces and multilayer spaces is considered. The algorithms of motion planning in generated environments are analyzed. The model implements algorithms for resolving collisions, simulating the dynamics of environmental properties and visualizing the results. The model allows you to simulate random and repetitive dynamic processes occurring in the environment of the robots' motions. The individual characteristics of the robot-environment interaction are set by the coefficients of the influence of space on the energy characteristics of the controlled object. The results of the research are the dependences of the calculation time on the size and type of the map, the use of which allows us to evaluate the computational complexity depending on the required detail of the task. The scope of the considered model is the analysis of the characteristics of the top-level control systems of a group of heterogeneous robots under conditions of spatial and situational uncertainty.

Key words
Trajectory planning, modeling environment, robots, spatial-situational uncertainty.

DOI
https://doi.org/10.31776/RTCJ.7405 

Bibliographic description
Motorin, D. (2019). The study of the polymodel complex of the motion planning system of a heterogeneous group of autonomous robots in conditions of spatial-situational uncertainty. Robotics and Technical Cybernetics, 7(4), pp.291-299.

UDC identifier:
004.942:007.52:519.876.5

References

  1. Karpov, V., Rovbo, M. and Ovsyannikova, E. (2018). Sistema modelirovaniya povedeniya grupp robototekhnicheskikh agentov s elementami sotsial'noi organizatsii Kvorum [Kvorum – the system for modeling the behavior of robotic agent groups with elements of social organization]. Programmnye produkty i sistemy [Software & Systems], 31(3), pp.581–590. (in Russian).
  2. Rovbo, M., Ovsyannikova, E. and Chumachenko, A. (2017). Obzor sredstv imitatsionnogo modelirovaniya kollektivov robotov s elementami sotsial'noi organizatsii [Review of simulation modeling tools for robot groups with social organization elements]. Programmnye produkty i sistemy [Software & Systems], 30(3), pp.425–434. (in Russian). DOI: 10.15827/0236-235X.030.3.425-434.
  3. Zhu, Z., Liu, S. and Zhang, B. (2011). Global path planning of mobile robot based on improved ant colony algorithm. In: Proceedings of the 30th Chinese Control Conference, Yantai, pp. 4083-4088. (in Chinese)
  4. Che, H., Wu, Z., Kang, R. and Yun, C. (2016). Global path planning for explosion-proof robot based on improved ant colony optimization. In: 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), Tokyo, pp.36-40. doi: 10.1109/ACIRS.2016.7556184
  5. Al Dabooni, S. and Wunsch, D. (2016). Heuristic dynamic programming for mobile robot path planning based on Dyna approach. In: 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, pp.3723-3730. doi: 10.1109/IJCNN.2016.7727679
  6. Ivanov, M., Sergiyenko, O., Tyrsa, V., Lindner, L., Rodriguez-Quiñonez, J., Flores-Fuentes, W., Rivas-Lopez, M., Hernández-Balbuena, D. and Nieto Hipólito, J. (2019). Wireless integration to optimize environmental recognition and calculate the trajectory of a group of robots. In: Trudy ISP RAN [Proc. ISP RAS], 31(2), pp.67-82. (in Russian). DOI: 10.15514/ISPRAS-2019-31(2)-6
  7. Ermolov, I., Ilyuhin, Y. and Sobol'nikov, S. (2012). Planirovanie traektorij dvizheniya v gruppe avtonomnyh mobil'nyh kommunikacionnyh robotov [Planning of motion trajectory in group of autonomous mobile communication robots]. Vestnik MGTU «Stankin», 4(23), pp.96-100. (in Russian).
  8. Pshikhopov, V. and Medvedev, M. (2018). Group Control of Autonomous Robots Motion in Uncertain Environment via Unstable Modes. SPIIRAS Proceedings. 5(60). pp.39-63. (in Russian). DOI 10.15622/sp.60.2
  9. Zenkevich, S., Hua Chzhu and Czjan'ven' Ho (2017). Dvizhenie gruppy mobil'nyh robotov v stroju tipa «konvoj» - teorija, modelirovanie i jeksperiment [Motion of mobile robots group in a convoy-type system - theory, simulating and experiment]. In: Chetvertyj vserossijskij nauchno-prakticheskij seminar «Bespilotnye transportnye sredstva s jelementami iskusstvennogo intellekta» (BTS-II-2017) [Fourth All-Russian Scientific and Practical Seminar «Unmanned Vehicles with Artificial Intelligence Elements»], Kazan', pp.136-147. (in Russian).
  10. Saprykin, R. (2015). Algoritmy informacionnogo vzaimodejstvija intellektual'nyh mobil'nyh robotov pri kartografirovanii vneshnej sredy funkcionirovanija [Algorithms of information interaction of intelligent mobile robots when mapping the external environment of functioning]. Izvestija JUFU. Tehnicheskie nauki, 03, pp.164-174. (in Russian).
  11. Wang, Z. and Xiang, X. (2018). Improved Astar Algorithm for Path Planning of Marine Robot. In: 2018 37th Chinese Control Conference (CCC), Wuhan, pp. 5410-5414. doi: 10.23919/ChiCC.2018.8483946
  12. Ding, H., Li, Y., Chai, Y. and Jian, Q. (2018). Path Planning for 2-DOF Manipulator Based on Bezier Curve and A* algorithm. In: 2018 Chinese Automation Congress (CAC), Xi'an, China, pp. 670-674. doi: 10.1109/CAC.2018.8623539
  13. Sakti, A., Majid, I., Cahyadi, A. and Ardiyanto, I. (2017). Path planning for holonomic mobile robot using arrival time field. In: 2017 International Conference on Computer, Control, Informatics and its Applications (IC3INA), Jakarta, pp. 111-114. doi: 10.1109/IC3INA.2017.8251750
  14. Ling, F., Du, C., Chen, J. and Yuan, Z. (2019). An Improved Geometrical Path Planning Algorithm for UAV in Irregular-obstacle Environment. In: 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Chongqing, China, pp. 972-976. doi: 10.1109/ITAIC.2019.8785442
  15. Huang, H. et al. (2019). Dynamic Path Planning Based on Improved D* Algorithms of Gaode Map. In: 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chengdu, China, pp. 1121-1124. doi: 10.1109/ITNEC.2019.8729438
  16. Motorin, D. and Popov, S. (2018). Multi-Criteria Path Planning Algorithm for a Robot on a Multilayer Map. Informatsionno-upravliaiushchie sistemy [Information and Control Systems], 3, pp.45–53. (in Russian). doi:10.15217/issn1684-8853.2018.3.45
  17. Motorin, D., Popov, S. and Kurochkin, L. (2017). An algorithm for collision avoidance in path planning for a group of robots in a spatio-situational indeterminacy. St. Petersburg State Polytechnical University Journal. Computer Science. Telecommunications and Control Systems, 10(2), pp.32–44. (in Russian). DOI: 10.18721/JCSTCS.10203
Editorial office address: 21, Tikhoretsky pr., Saint-Petersburg, Russia, 194064, tel.: +7(812) 552-13-25 e-mail: zheleznyakov@rtc.ru