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Volume 7 Issue 5
Sep.  2020

IEEE/CAA Journal of Automatica Sinica

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Abenezer Girma, Niloofar Bahadori, Mrinmoy Sarkar, Tadewos G. Tadewos, Mohammad R. Behnia, M. Nabil Mahmoud, Ali Karimoddini and Abdollah Homaifar, "IoT-Enabled Autonomous System Collaboration for Disaster-Area Management," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1249-1262, Sept. 2020. doi: 10.1109/JAS.2020.1003291
Citation: Abenezer Girma, Niloofar Bahadori, Mrinmoy Sarkar, Tadewos G. Tadewos, Mohammad R. Behnia, M. Nabil Mahmoud, Ali Karimoddini and Abdollah Homaifar, "IoT-Enabled Autonomous System Collaboration for Disaster-Area Management," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1249-1262, Sept. 2020. doi: 10.1109/JAS.2020.1003291

IoT-Enabled Autonomous System Collaboration for Disaster-Area Management

doi: 10.1109/JAS.2020.1003291
Funds:  This work was supported partially by Air Force Research Laboratory, the Office of the Secretary of Defense (OSD) (FA8750-15-2-0116), the National Science Foundation (NSF) (1832110), and the National Institute of Aerospace and Langley (C16-2B00-NCAT)
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  • Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits cause delays in response time, resulting in fatality and property damage. In this paper, we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster. The framework consists of unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), a cloud-based remote control station (RCS). A light-weight message queuing telemetry transport (MQTT) based communication is adopted for facilitating collaboration between autonomous systems. To effectively work under unfavorable disaster conditions, antenna tracker is developed as a tool to extend network coverage to distant areas, and mobile charging points for the UAVs are also implemented. The proposed framework’s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language (AADL). Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols, and the implemented UAV control mechanisms are functioning properly. Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.


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    2 https://clearpathrobotics.com/jackal-small-unmanned-ground-vehicle/
    3 https://www.vicon.com
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    6 https://osate.org/
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    • Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits still cause delays in response time that results in fatality and property damages. In this paper, we proposed and implemented a framework designed to create a collaborative effort between heterogeneous Unmanned Vehicles and first-responders to make search and rescue operations safer and faster.
    • The proposed collaborative heterogeneous autonomous system framework consists of Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), cloud-based Remote-Control Station (RCS) IoT technology, cloud connectivity, and antenna tracker.
    • An effective UAV resource allocation mechanism is implemented using a clustering algorithm technique for maximizing the UAVs’ network coverage area and an antenna tracker is developed to extend network coverage to the UAVs and.
    • A control mechanism for landing UAV on moving UGV platform is implemented for recharging UAVs as well as to transport them.
    • Advanced Architectural Design Language (AADL) is used to analyze and evaluate the end-to-end delay of the proposed framework. To the best of our knowledge, this is the first work that uses AADL for timing analysis in an IoT-enabled autonomous system.


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