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Disaster management information system for disaster management

Full project name:  Information System of Emergency Situations Management in the areas of  Floods and Landslides with Assistance of Distributed Heterogeneous Group of Robots.

The LIRS team, led by Professor Evgeni Magid, who has extensive international experience in universities and research institutes in the field of search and rescue robotics (Tsukuba University, Carnegie Mellon University, University of Bristol, etc.),  for 3 years will be implementing a project on “Information System for Emergency Situations Management in Floods and Landslides with Assistance of Distributed Heterogeneous Group of Robots” in a collaboration with two teams - from Japan and under the management of Professor Fumitosi Matsuno, Kyoto University (Kyoto University), which is the 35th place in the QS World University Ranking and with a team from Thailand under the guidance of Professor Jackrit Sutkorn, Mahidol University, which is 380 place in the QS World University Ranking. 

Figure 1 presents the general idea of ​​the proposed project. Heterogeneous groups of robots will work as separate national teams (which in turn may be divided into distributed subgroups), supplying data to a centralized information system for emergency management. The robots will perform the tasks of building thematic maps of the disaster area from the surface of the water, under the water, from the air and from the ground, including observation of the destroyed buildings. Figure 2 shows the distribution of independent tasks between national teams and their interaction by common tasks within the project. 

Fig. 1 Heterogeneous distributed groups of robots collect the information necessary to create separate thematic maps, which will then be combined into a multi-layered map of the disaster zone.

Fig. 2. The proposed information system and plan for joint research: the R symbol define tasks of the Russian team, J - the tasks of the Japanese team, T - tasks of the Thai team.

In Asia, including the Asian part of the Russian Federation, there is a high level of risk of natural disasters, among which floods are the most frequent and the most severe losses in terms of casualties and the economy. Therefore, the development of an information system (IS) for managing a disaster management process, which makes it possible to increase the effectiveness and speed of elimination of consequences, is today one of the most pressing and sought-after tasks facing the scientific community.

Three countries participating in the project - the Russian Federation, Thailand and Japan - at certain times of the year are at risk of floods and landslides caused by torrential rains and the rapid melting of large amounts of snow cover. Using the long-term experience of our three national teams in search and rescue robotics for disaster management, the proposed project will develop a robotic information collection IC for effective disaster management in a disaster zone. The main objective of the project is the development and testing of a prototype IP, which can then become an international standard for the elimination of both national and international natural disasters.

The IS will collect data using distributed heterogeneous groups of robotic complexes, including various types of unmanned aerial vehicles (UAV), unmanned ground robots (UGV), autonomous crewless ships (ACS) and autonomous underwater vehicle (AUV). Separate maps built by distributed groups of robots will be combined into a single multi-layer thematic map of the disaster area, which will help search and rescue teams to speed up the evacuation of survivors, assess the risk of further destruction of buildings and environmental pollution, which in turn will significantly increase the chances of rescuing survivors and increase the safety of rescuers during search operations.

The new control strategies, interfaces, protocols, robot models, algorithms and software developed by the project will be tested both with the help of simulation and in the framework of field experiments. To demonstrate the effectiveness of the IS developed in the framework of the project, its testing will be conducted in cooperation with the local authorities of each of the three countries. As a result of the project, an understanding of the mechanisms associated with technologically sound decision making for effective emergency management will be improved. The development and implementation of a new generation of robotic tools for disaster management, which are in great demand by international and national emergency agencies, will make a huge contribution to the scientific, technological and industrial development of society.

Publications on Project: 

  1. Magid E., Pashkin A., Simakov N., Abbyasov B., Suthakorn J., Svinin M. and Matsuno F. Artificial intelligence based framework for robotic search and rescue operations conducted jointly by international teams // 14th International Conference on Electromechanics and Robotics "Zavalishin's Readings" (Kursk, Russia; 17-20 April 2019) - p. 15-26.
  2. Moskvin, I., Lavrenov, R. (2019). Modelling Tracks and Controller for Servosila Engineer Robot. Proceedings of 14th International Conference on Electromechanics and Robotics "Zavalishin's Readings", 154, p. 411-422.
  3. Magid E., Tsoy T., Matsuno F., Suthakorn J., Svinin M. (2019). Disaster Risk and Reduction Management with Search and Rescue Robotics Approach. The 2019 International Workshop of ICAROB in Taiwan (2019 ICAROB Taiwan).
  4. Simakov N., Lavrenov R., Zakiev A., Safin R., Martinez-Garcia E.A. Modeling USAR maps for the collection of information on the state of the environment // The 12th International Conference on the Developments in eSystems Engineering (Kazan, Russia; 7-10 October 2019).
  5. Pashkin A., Lavrenov R., Zakiev A., Svinin M. Pilot communication protocols for group of mobile robots in USAR scenarios // The 12th International Conference on the Developments in eSystems Engineering (Kazan, Russia; 7-10 October 2019).
  6. Zakiev A. Partially unknown environment exploration algorithm for a mobile robot / Lavrenov R., Magid E., Svinin M., Matsuno F. // Journal of Advanced Research in Dynamical and Control Systems. - 2019. - Vol. 11(08). - p. 1743-1753.
  7. Denisov E., Sagitov A., Yakovlev K., Su K.-L., Svinin M., Magid E. Towards Total Coverage in Autonomous Exploration for UGV in 2.5D Dense Clutter Environment // The 16th International Conference on Informatics in Control, Automation and Robotics (Prague, Czech Republic; 29-31 July 2019) - p. 409-416.
  8. Denisov, E., Sagitov, A., Lavrenov, R., Su, K.-L., Svinin, M., Magid, E. (2019). DCEGen: Dense Clutter Environment Generation Tool for Autonomous 3D Exploration and Coverage Algorithms Testing. Lecture Notes in Computer Science, 11659, p. 216-225.
  9. Шабалина К.С., Сагитов А.Г., Магид Е.А. Моделирование мобильного робота Аврора Юниор в среде ROS/GAZEBO // V Всероссийский научно-практический семинар «Беспилотные транспортные средства с элементами искусственного интеллекта» (БТС-ИИ-2019), (г. Санкт-Петербург, Россия; 22-24 мая 2019) - c. 221-229.
  10. Лавренов Р.О., Магид Е.А., Мацуно Ф., Свинин М.М., Сутакорн Дж. Разработка и имплементация сплайн-алгоритма планирования пути в среде ROS/Gazebo // Труды СПИИРАН, 18(1) (г. Санкт-Петербург) - с. 57-84.
  11. Имамеев Д.Т., Лавренов Р.О., Сагитов А.Г., Шабалина К.С., Магид Е.А., Мартинес-Гарсия Э.А., Су К.-Л. Разработка процедуры автономной параллельной парковки мобильного робота Unior // Международная научно-техническая конференция "ИНТЕРСТРОЙМЕХ - 2019" (г. Казань, Россия; 12-13 сентября 2019) - с. 58.
  12. Никифоров Н.А., Лавренов Р.О., Сагитов А.Г., Шабалина К.С., Магид Е.А., Свинин М.М., Хсиа К.-Х. Сравнительный анализ алгоритмов распознавания дорожных знаков для беспилотного автомобиля Unior компании Avrora Robotics // Международная научно-техническая конференция "ИНТЕРСТРОЙМЕХ - 2019" (г. Казань, Россия; 12-13 сентября 2019) - с. 62.
  13. Сафин Р.Н., Цой Т.Г., Лавренов Р.О., Магид Е.А. Разработка системы оптимальной передачи видеоданных с камер мобильного робота “Сервосила Инженер” // XIV Всероссийская научно-практическая конференция «Перспективные системы и задачи управления», с. 304-313.