Towards enabling distributed situational awareness for autonomous system collaboration
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State of the art research towards multi-agent AI requires the ability to perceive within a given environment. This involves a process of ingesting raw information streams into explainable representation of the surrounding environment. This process may be referred to as achieving situational awareness. These information streams are often singular, reducing information to what is relevant for a targeted sensor context, which limits their ability to allow multiple autonomous platforms to perceive based on the total available information. There are many domains where situation awareness is necessary, such as in search and rescue context to effectively triage autonomous agent efforts. To enable distributed situational awareness, herein we present the steps adopted to standardize the management of information streams across contexts of varying sensor domains, the process of investigating the validity of this system, and the additional infrastructure that has helped facilitate situational awareness. This system is enabled through the Robot Operating System 2 (ROS 2), which we outline the steps taken to evaluate it within a distributed context, such as communication performance, sensor processing, and infrastructure management. Based on ROS 2's system components, we show a system that enables sensor information to retain its generalized form, which other platforms can manipulate for their targeted need without the unnecessary destruction of data to perceive within its system. We seek to establish a meaningful connection from the concepts of autonomous agent collaboration research to be practically applied.
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M.S.