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Beehive-Inspired Information Gathering with a Swarm of Autonomous Drones.

Alberto ViserasThomas WiedemannChristoph ManssValentina KaroljDmitriy Shutin And Juan Marchal
Published in: Sensors (Basel, Switzerland) (2019)
This paper presents a beehive-inspired multi-agent drone system for autonomous information collection to support the needs of first responders and emergency teams. The proposed system is designed to be simple, cost-efficient, yet robust and scalable at the same time. It includes several unmanned aerial vehicle (UAVs) that can be tasked with data collection, and a single control station that acts as a data accumulation and visualization unit. The system also provides a local communication access point for the UAVs to exchange information and coordinate the data collection routes. By avoiding peer-to-peer communication and using proactive collision avoidance and path-planning, the payload weight and per-drone costs can be significantly reduced; the whole concept can be implemented using inexpensive off-the-shelf components. Moreover, the proposed concept can be used with different sensors and types of UAVs. As such, it is suited for local-area operations, but also for large-scale information-gathering scenarios. The paper outlines the details of the system hardware and software design, and discusses experimental results for collecting image information with a set of 4 multirotor UAVs at a small experimental area. The obtained results validate the concept and demonstrate robustness and scalability of the system.
Keyphrases
  • health information
  • electronic health record
  • big data
  • emergency department
  • public health
  • climate change
  • data analysis
  • body mass index