Amanda Prorok

About

Amanda Prorok is a leading researcher in multi-robot systems, whose work spans decentralized path planning, resilient robot coordination, and learning-based communication for autonomous systems. Her research addresses some of the most pressing challenges in robotics: how teams of robots can efficiently navigate dynamic environments, coordinate without centralized control, and remain robust in the face of malfunctioning or malicious agents. Prorok's most influential contributions leverage graph neural networks to enable scalable, decentralized multi-robot path planning — work that has collectively garnered hundreds of citations, with her 2020 papers on reinforcement learning-based path planning and GNN-based coordination attracting over 340 and 260 citations respectively. Her pioneering work on resilient flocking and formation control (193 citations) introduced graph-theoretic principles to protect robot teams against noncooperative agents, a challenge with profound implications for real-world deployments. Her 2022 critical review of communications in multi-robot systems reflects her broad perspective on the field's infrastructure needs. Beyond planning and resilience, Prorok has made notable contributions to heterogeneous swarm control, collaborative localization, and ultra-wideband indoor positioning. Across all these areas, her research consistently bridges theoretical rigor with practical applicability, making her work essential reading for anyone interested in the future of autonomous multi-robot systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Mobile Robot Path Planning in Dynamic Environments Through Globally Guided Reinforcement Learning

   343 citations · 2020
2. 2
   Graph Neural Networks for Decentralized Multi-Robot Path Planning

   263 citations · 2020
3. 3
   Resilient Flocking for Mobile Robot Teams

   193 citations · 2017
4. 4
   Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planning

   182 citations · 2021
5. 5
   Resilient consensus for time-varying networks of dynamic agents

   126 citations · 2017
6. 6
   A Critical Review of Communications in Multi-robot Systems

   125 citations · 2022
7. 7
   Formations for Resilient Robot Teams

   93 citations · 2017
8. 8
   The Impact of Diversity on Optimal Control Policies for Heterogeneous Robot Swarms

   83 citations · 2017
9. 9
   Low-cost collaborative localization for large-scale multi-robot systems

   75 citations · 2012
10. 10
    Accurate indoor localization with ultra-wideband using spatial models and collaboration

    63 citations · 2013

Key Collaborators

Contact & Links