Abstract
An important application of cooperative robotics is search and rescue of victims in disaster zones. The cooperation between robots requires multiple factors that need to be taken into consideration such as communication between agents, distributed control, power autonomy, cooperation, navigation strategy, locomotion, among others. This work focuses on navigation strategy with obstacles avoidance and victims localization. The strategy used for navigation is based on swarm theory where each robot is an swarm agent. The calculation of attraction and repulsion forces used to keep the swarm compact is used to avoid obstacles and attract the swarm to the victim zones. Additionally, an agent separation behavior is added, so the swarm can leave behind the agents, who found victims so these can support the victims by transmitting their location to a rescue team. Several experiments were performed to test navigation, obstacle avoidance and victims search. The results show how the swarm theory meets the requirements of navigation and search operations of cooperative robots.
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León, J., Cardona, G.A., Botello, A., Calderón, J.M. (2017). Robot Swarms Theory Applicable to Seek and Rescue Operation. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_104
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DOI: https://doi.org/10.1007/978-3-319-53480-0_104
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