MaryAnne Fields
Papers
13
Total Citations
418
H-Index
8
About
Maryanne Fields is a leading researcher in swarm robotics and human-swarm interaction, with a career focused on developing control strategies for unmanned vehicle teams. Her primary contributions lie in formation control using artificial potential fields, where she pioneered techniques that organize swarms of robots into precise geometric formations by constructing virtual surfaces from normal, sigmoid, and bivariate normal functions. Her two most-cited papers, "Unmanned ground vehicle swarm formation control using potential fields" (132 citations) and "Swarm Formation Control Utilizing Elliptical Surfaces and Limiting Functions" (131 citations), established foundational methods for controlling swarm geometry and individual member spacing while enabling obstacle avoidance. Fields has also made significant advances in heterogeneous swarms, coordinating unmanned ground vehicles with aerial systems, and in soldier-swarm interaction—designing interfaces and algorithms that allow human operators to effectively supervise and correct swarm actions in degraded battlefield conditions. Her work on multimodal controls and extreme scalability addresses critical Army needs for convoy security and situational awareness. With over 400 total citations across her publications, Fields continues to shape the field of autonomous robotic swarms, bridging theoretical control methods with practical military applications.
Research Focus
Key Achievements
Top Papers
- 1Unmanned ground vehicle swarm formation control using potential fields132 citations · 2007
- 2Swarm Formation Control Utilizing Elliptical Surfaces and Limiting Functions131 citations · 2009
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- 5Effective robot team control methodologies for battlefield applications28 citations · 2009
- 6Swarm formation control utilizing ground and aerial unmanned systems18 citations · 2008
- 7Multimodal controls for soldier/swarm interaction15 citations · 2011
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- 9Simulation tools for robotics research and assessment8 citations · 2016
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