Multi-agent Coordination for On-Demand Data Gathering with Periodic Information Upload

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Abstract

In this paper we develop a method for planning and coordinating a multi-agent team deployment to periodically gather information on demand. A static operation center (OC) periodically requests information from changing goal locations. The objective is to gather data in the goals and to deliver it to the OC, balancing the refreshing time and the total number of information packages. The system automatically splits the team in two roles: workers to gather data, or collectors to retransmit the data to the OC. The proposed three step method: (1) finds out the best area partition for the workers; (2) obtains the best balance between workers and collectors, and with whom the workers must to communicate, a collector or the OC; (3) computes the best tour for the workers to visit the goals and deliver them to the OC or to a collector in movement. The method is tested in simulations in different scenarios, providing the best area partition algorithm and the best balance between collectors and workers.

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APA

Marchukov, Y., & Montano, L. (2019). Multi-agent Coordination for On-Demand Data Gathering with Periodic Information Upload. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11523 LNAI, pp. 153–167). Springer Verlag. https://doi.org/10.1007/978-3-030-24209-1_13

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