WeA03 - COIN: COmmunication-aware INtegrated learning, estimation, and control

Future autonomous systems ranging from multi robot networks to distributed satellite constellations must operate reliably under limited, delayed, and lossy communications. 
Traditional control and learning frameworks, however, assume perfect information flow, leaving a fundamental gap between the theory and the realities of modern cyber-physical systems. This tutorial introduces a unified framework for communication-constrained learning, estimation, and control, where sensing, estimation, learning, and decision-making are tightly coupled through shared, resource-limited communication channels. We discuss the theoretical foundations of system identification under communication constraints, highlighting recent advances in operator-theoretic and learning-enabled modeling that yield provable performance guarantees even with degraded data. The second part focuses on communication-aware control design, covering sequential and joint control–communication co design, adaptive quantization, and risk-aware robust control under asymmetric information. 

We demonstrate how these theories enable resilient guidance and control in robotics, autonomous driving, and space applications where nonlinear dynamics, limited bandwidth, and high-latency links pose critical challenges to autonomy. The tutorial combines theory, algorithms, and case studies to provide attendees with (i) a principled understanding of the quality–quantity trade-off in data-driven control, (ii) practical tools for implementing communication-aware dynamics learning framework, estimators, and controllers, and (iii) insights into emerging aerospace, autonomous cars, and robotic applications where these ideas are reshaping design paradigms.

Schedule of Talks