Event Overview
Multi-agent coverage optimization is a foundational problem with applications across surveillance, wireless network design, data harvesting, and Mobility-on-Demand (MoD) systems. Historically, the Voronoi partitioning method and its variations have dominated solutions to this problem. We argue that this classic paradigm is inadequate for modern challenges, which involve heterogeneous sensor quality and complex utility derived from overlapping coverage and introduce a new deployment framework that moves beyond spatial partitioning by formulating the task as a set of combinatorial assignment problems. We demonstrate how leveraging powerful, established techniques—specifically Maximum Bipartite Matching and Submodular Maximization—provides a mathematically rigorous path to deriving provably efficient, near-optimal deployment strategies.
Solmaz S. Kia is a Professor of Mechanical and Aerospace Engineering at UCI, with a joint appointment in Computer Science. She obtained her PhD in Mechanical and Aerospace Engineering from UCI, in 2009, and her M.Sc. and B.Sc. in Aerospace Engineering from the Sharif University of Technology, Iran, in 2004 and 2001, respectively. She was a senior research engineer at SySense Inc. from 2009 to 2010 and held postdoctoral positions in the Department of Mechanical and Aerospace Engineering at boththe University of California San Diego and UCI. She was a recipient of the UC president’s post-doctoral fellowship in 2012–2014, an NSF CAREER award in 2017, Control Systems Magazine best paper award in 2021. She is a senior member of IEEE and an associate editor for Automatica, IEEE Transactions on Control of Network Systems and IEEE Open Journal of Control Systems. Her research interests include distributed ptimization, coordination, estimation algorithm design; and probabilistic multi-agent robotics navigation and motion planning.
