• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.156-161
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• 2020

In an environment that operates multiple UAVs, the use of a decentralized task allocation algorithm has more robustness from a single failure of UAV on the mission because there is no central command center. In addition, UAVs have situational awareness and redistribute tasks among themselves, which can expand the mission range. The use of multiple UAVs in a mission has increased as the agent hardware has decreased in size and cost. The decentralized mission-planning algorithm has the advantages of a larger mission range and robustness to a single failure during the mission. This paper extended the type of mission the uses CBBA, which is the most well-known decentralized task allocation algorithm, to the point mission and en-route mission. This will describe the real mission situation that has the purpose of surveillance. A Monte-Carlo simulation was conducted in the case of multiple agents in the task-rich environment, and the global rewards of each case were compared.