Wild Swarms: Autonomous Drones for Environmental Monitoring and Protection

Fabrice Saffre (Corresponding author), Hannu Karvonen, Hanno Hildmann

Research output: Chapter in Book/Report/Conference proceedingChapter or book articleScientificpeer-review


In this paper, we present an example case study of how an autonomous swarm-based Multi-Robot System (MRS) could contribute to environmental protection. Our proof-of-concept simulation involves using a collective intelligence framework to manage a drone swarm tasked with protecting a wilderness area over a long period of time. In the proposed ambitious and futuristic Concept of Operation (ConOps), a self-sufficient and self-organizing colony of “drone wardens” is left to autonomously plan and execute thousands of individual reconnaissance missions, attempting to maintain the best possible situational awareness while simultaneously managing its resources and responding to relevant actors and events in the environment. Specifically, we have devised a scenario in which two types of external actors (hikers (blue team) and bears (red team)) should elicit a different collective response from the swarm: whilst the former should only be checked on from time to time to ensure their safety, the latter should be monitored continuously during their crossing of the park. Numerical experiments, in which a variety of simple but robust decision-making algorithms were tested, demonstrate our system’s ability to support the relevant swarming behaviour, such as efficient division of labour and recruitment, in the pursuit of this mission.
Original languageEnglish
Title of host publicationNew Developments and Environmental Applications of Drones
Subtitle of host publicationFinDrones 2023
Number of pages32
ISBN (Electronic)978-3-031-44607-8
ISBN (Print)978-3-031-44606-1
Publication statusPublished - 2024
MoE publication typeA3 Part of a book or another research book
EventFinDrones 2023 - IoT Cmapus, Salo, Finland
Duration: 15 Feb 202316 Feb 2023


ConferenceFinDrones 2023
Internet address


This research is funded by Academy of Finland (project grant number (348010) and conducted as part of the Unmanned Aerial Systems based solutions for real-time management of wildfires (FireMan) project. This research was also partly supported by the Academy of Finland project “Finnish UAV Ecosystem” (FUAVE, project grant number 337878).


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