Real-time remote tracking using under-sampled and delayed measurements is considered here. We study an autonomous system where a transmitter monitors the evolution of a discrete Markov source and sends status updates to a destination over an unreliable wireless channel. The destination is tasked with real-time source reconstruction for remote actuation. We introduce new goal-oriented sampling and communication policies, which leverage the significance and effectiveness of messages, as a means to generate and transmit only the most “informative” samples for real-time actuation. Our results illustrate that semantics-empowered policies significantly reduce both the real-time reconstruction and the cost of actuation errors, as well as the amount of ineffective updates.
Goal-oriented communication for real-time tracking in autonomous systems
ICAS 2021, IEEE 1st International Conference on Autonomous Systems, 10-13 August 2021, (Virtual Conference)
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