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Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms

Centre for Automation and Robotics (CAR), Technical University of Madrid (UPM), 28006 Madrid , Spain
Author to whom correspondence should be addressed.
Current address: C/ José Gutiérrez Abascal, 2, 28006 Madrid, Spain.
Appl. Sci. 2018, 8(5), 711;
Received: 24 March 2018 / Revised: 24 April 2018 / Accepted: 2 May 2018 / Published: 3 May 2018
(This article belongs to the Special Issue Swarm Robotics)
PDF [1000 KB, uploaded 3 May 2018]


The search of a given area is one of the most studied tasks in swarm robotics. Different heuristic methods have been studied in the past taking into account the peculiarities of these systems (number of robots, limited communications and sensing and computational capacities). In this work, we introduce a behavioral network made up of different well-known behaviors that act together to achieve a good performance, while adapting to different scenarios. The algorithm is compared with six strategies based on movement patterns in terms of three performance models. For the comparison, four scenario types are considered: plain, with obstacles, with the target location probability distribution and a combination of obstacles and the target location probability distribution. For each scenario type, different variations are considered, such as the number of agents and area size. Results show that although simplistic solutions may be convenient for the simplest scenario type, for the more complex ones, the proposed algorithm achieves better results. View Full-Text
Keywords: swarm robotics; search; surveillance; behaviors; patterns; comparison swarm robotics; search; surveillance; behaviors; patterns; comparison

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Garcia-Aunon, P.; Barrientos Cruz, A. Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms. Appl. Sci. 2018, 8, 711.

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