Optimized Path Planning for Inspection by Unmanned Aerial Vehicles Swarm with Energy Constraints
| Autor: | Momena Monwar, Omid Semiari, Walid Saad |
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| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
Computer science Real-time computing Swarm behaviour 020206 networking & telecommunications ComputerApplications_COMPUTERSINOTHERSYSTEMS 0102 computer and information sciences 02 engineering and technology Energy consumption Systems and Control (eess.SY) 01 natural sciences 7. Clean energy Base station Computer Science - Robotics 010201 computation theory & mathematics Path (graph theory) 0202 electrical engineering electronic engineering information engineering FOS: Electrical engineering electronic engineering information engineering Computer Science - Systems and Control Motion planning Time complexity Robotics (cs.RO) Energy (signal processing) |
| Zdroj: | GLOBECOM |
| DOI: | 10.48550/arxiv.1808.06018 |
| Popis: | Autonomous inspection of large geographical areas is a central requirement for efficient hazard detection and disaster management in future cyber-physical systems such as smart cities. In this regard, exploiting unmanned aerial vehicle (UAV) swarms is a promising solution to inspect vast areas efficiently and with low cost. In fact, UAVs can easily fly and reach inspection points, record surveillance data, and send this information to a wireless base station (BS). Nonetheless, in many cases, such as operations at remote areas, the UAVs cannot be guided directly by the BS in real-time to find their path. Moreover, another key challenge of inspection by UAVs is the limited battery capacity. Thus, realizing the vision of autonomous inspection via UAVs requires energy-efficient path planning that takes into account the energy constraint of each individual UAV. In this paper, a novel path planning algorithm is proposed for performing energy-efficient inspection, under stringent energy availability constraints for each UAV. The developed framework takes into account all aspects of energy consumption for a UAV swarm during the inspection operations, including energy required for flying, hovering, and data transmission. It is shown that the proposed algorithm can address the path planning problem efficiently in polynomial time. Simulation results show that the proposed algorithm can yield substantial performance gains in terms of minimizing the overall inspection time and energy. Moreover, the results provide guidelines to determine parameters such as the number of required UAVs and amount of energy, while designing an autonomous inspection system. Comment: IEEE Global Communications Conference (GLOBECOM), Ad Hoc and Sensor Networks Symposium |
| Databáze: | OpenAIRE |
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