Multi-robot team formation control in the GUARDIANS project

SAEZ-PONS, Joan, ALBOUL, Lyuba, PENDERS, Jacques and NOMDEDEU, Leo (2010). Multi-robot team formation control in the GUARDIANS project. Industrial Robot, 37 (4), 372-383.


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The GUARDIANS multi-robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots guide and accompany the firefighters on site whilst indicating possible obstacles and the locations of danger and maintaining communications links.


In order to fulfill the aforementioned tasks the robots need to exhibit certain behaviours. Among the basic behaviours are capabilities to stay together as a group, that is, generate a formation and navigate while keeping this formation. The control model used to generate these behaviours is based on the so-called social potential field framework, which we adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots.


The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus the application has forced us to redefine the concept of a formation. Using the graph-theoretic terminology, we can say that a formation may be stretched out as a path or be compact as a star or wheel. We have implemented the developed behaviours in simulation environments as well as on real ERA-MOBI robots commonly referred to as Erratics. We discuss advantages and shortcomings of our model, based on the simulations as well as on the implementation with a team of Erratics.

Item Type: Article
Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Sheaf Solutions
Identification Number:
Page Range: 372-383
Depositing User: Jacques Penders
Date Deposited: 14 Sep 2011 15:19
Last Modified: 18 Mar 2021 14:31

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