Multi-Robot Systems for Environmental Monitoring and Intervention

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "AI in Robotics".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 648

Special Issue Editors


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Guest Editor
1. LITIS Laboratory, Normandy University of Le Havre, Le Havre, Normandy, France
2. Faculty of Mathematics and Natural Sciences, Cardinal Stefan Wyszynski University, 01-815 Warsaw, Poland
Interests: interaction networks; dynamic graphs; nature-inspired comp.; complex systems; swarm robotics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Research Group in Electrotechnics and Automatics (GREAH), Universite du Havre Normandie, Le Havre, France
Interests: advanced automatic control and its applications to mobile robotics and electrical engineering

Special Issue Information

Dear Colleagues,

Multi-robot systems are versatile tools that can continuously monitor environmental conditions in real time, collecting data on factors such as pollution, temperature, and biodiversity, crucial for understanding ecological dynamics. Combining observation and action, multi-robot systems can detect changes and threats while simultaneously intervening with operations like pollution mitigation, habitat enhancement, waste management, or disaster response. The following robot types will be considered for this Special Issue:

(i) Unmanned aerial vehicles (UAVs) can be used for remote or difficult-to-reach areas. Equipped with relevant sensors, they can monitor large areas, track wildlife, map ecosystems, detect changes in vegetation, or monitor air quality.

(ii) Unmanned Ground Vehicles (UGVs) are suitable for land operations, can survey landscapes, detect soil conditions (soil sampling), and gather data on ground-level pollutants. They can also collect trash, especially in hazardous areas, and support, together with UAVs, search-and-rescue missions.

(iii) Autonomous Underwater Vehicles (AUVs) can monitor, explore, and map underwater ecosystems, monitor coral reefs, track marine life, and measure temperature, pH, and pollution levels. They can actively engage in environmental restoration and protection efforts, like, for instance, remove plastics, transplant coral and marine vegetation, monitor human installation like pipeline for preventing leaks and pollution.

This Special Issue welcomes original research papers dealing with any aspect of multi-robot systems’ environmental monitoring and engagement.

Prof. Dr. Frédéric Guinand
Dr. Francois Guerin
Guest Editors

Manuscript Submission Information

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Keywords

  • multi-robot systems
  • MRS
  • UAV
  • UGV
  • AUV
  • environment monitoring
  • data collection
  • remediation
  • pollution mitigation
  • tracking

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Published Papers (1 paper)

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25 pages, 3468 KiB  
Article
Distributed Monitoring of Moving Thermal Targets Using Unmanned Aerial Vehicles and Gaussian Mixture Models
by Yuanji Huang, Pavithra Sripathanallur Murali and Gustavo Vejarano
Robotics 2025, 14(7), 85; https://doi.org/10.3390/robotics14070085 - 22 Jun 2025
Viewed by 164
Abstract
This paper contributes a two-step approach to monitor clusters of thermal targets on the ground using unmanned aerial vehicles (UAVs) and Gaussian mixture models (GMMs) in a distributed manner. The approach is tailored to networks of UAVs that establish a flying ad hoc [...] Read more.
This paper contributes a two-step approach to monitor clusters of thermal targets on the ground using unmanned aerial vehicles (UAVs) and Gaussian mixture models (GMMs) in a distributed manner. The approach is tailored to networks of UAVs that establish a flying ad hoc network (FANET) and operate without central command. The first step is a monitoring algorithm that determines if the GMM corresponds to the current spatial distribution of clusters of thermal targets on the ground. UAVs make this determination using local data and a sequence of data exchanges with UAVs that are one-hop neighbors in the FANET. The second step is the calculation of a new GMM when the current GMM is found to be unfit, i.e., the GMM no longer corresponds to the new distribution of clusters on the ground due to the movement of thermal targets. A distributed expectation-maximization algorithm is developed for this purpose, and it operates on local data and data exchanged with one-hop neighbors only. Simulation results evaluate the performance of both algorithms in terms of the number of communication exchanges. This evaluation is completed for an increasing number of clusters of thermal targets and an increasing number of UAVs. The performance is compared with well-known solutions to the monitoring and GMM calculation problems, demonstrating convergence with a lower number of communication exchanges. Full article
(This article belongs to the Special Issue Multi-Robot Systems for Environmental Monitoring and Intervention)
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