Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms
AbstractThe 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
A printed edition of this Special Issue is available here.
Share & Cite This Article
Garcia-Aunon, P.; Barrientos Cruz, A. Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms. Appl. Sci. 2018, 8, 711.
Garcia-Aunon P, Barrientos Cruz A. Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms. Applied Sciences. 2018; 8(5):711.Chicago/Turabian Style
Garcia-Aunon, Pablo; Barrientos Cruz, Antonio. 2018. "Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms." Appl. Sci. 8, no. 5: 711.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.