Multi-Agent Data Collection with Distributed Stochastic Coordination for Wireless Data Delivery
Robert T. Lattus, John M. Shea · 2025
We consider a scenario in which multiple mobile agents are tasked with moving around an area to collect data about some phenomena that occur at random within the prescribed area. The agents must deliver the data by traveling to a location inside the communication range of one of several access points (APs). We consider a fully decentralized setting, in which agents first randomly search the region for phenomena of interest and independently make choices about which APs to travel to once they have data to deliver. In this scenario, multiple agents that observe the same phenomenon may travel to a single AP that they characterize as most ideal, such as in terms of distance or communication capacity. This can cause delays in delivering the data if the communication capacity of the selected AP has to be shared among the agents. If centralized control were used, agents would be assigned to different APs to avoid these delays. We explore the use of stochastic policies to facilitate a form of distributed coordination and demonstrate their advantage over deterministic policies in a simulated environment.