Anthony Goeckner

Northwestern University, Northrop Grumman (United States)

Papers

Total Citations

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About

Anthony Goeckner is a rising leader in multi-agent systems and resilient swarm robotics, whose work directly addresses the fragility of real-world robot coordination. His research centers on developing algorithms that enable robot teams to maintain performance even when individual agents fail or communication links are disrupted—a critical capability for field robotics and defense applications. His most cited work (2024, 14 citations) introduces a graph neural network-based multi-agent reinforcement learning framework that makes distributed coordination resilient to agent attrition and communication disturbances, a significant advance over brittle traditional approaches. Goeckner also led the development of the Rapid Integration Swarming Ecosystem (RISE), a platform enabling large-scale field testing of swarm robotics for urban environments (2023, 6 citations), bridging the gap between theoretical swarming concepts and real-world deployment. His work on attrition-aware adaptation for multi-agent patrolling (2024, 4 citations) provides rare performance guarantees for systems facing agent loss, addressing a critical gap in surveillance and intrusion detection domains. Through these contributions, Goeckner is shaping the future of resilient, deployable multi-robot systems.