Sean B. Andersson

Boston University, University of Maryland, College Park

Papers

20

Total Citations

539

H-Index

13

About

Sean B. Andersson is a robotics and control systems researcher whose work sits at the dynamic intersection of formal methods, probabilistic systems, and autonomous robot navigation. He is best known for pioneering computational frameworks that enable robots to execute complex tasks specified through temporal logic while providing rigorous probabilistic satisfaction guarantees — a contribution that has proven foundational in the field, with his landmark 2011 paper accumulating 148 citations and its 2010 predecessor drawing 104 more. Andersson's research addresses one of autonomous robotics' central challenges: bridging the gap between high-level task specifications and reliable low-level control in uncertain, noisy environments. By modeling robot motion as Markov decision processes governed by Probabilistic Computation Tree Logic and related formalisms, his work enables provably correct behavior even under sensor and actuator uncertainty. He has further extended these frameworks to unknown and dynamic environments, demonstrating sustained innovation across a decade of research. Beyond formal methods, Andersson has contributed to biologically inspired acoustic sensing, developing sound-source localization systems that mimic natural hearing for robot phonotaxis, and to geometric problems such as the optimal discretization of continuous curves. His broad technical range, combined with consistent citation impact, marks him as a versatile and influential figure in autonomous systems research.

Research Focus

Key Achievements

13
H-Index
20
Papers
539
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Temporal Logic Motion Planning and Control With Probabilistic Satisfaction Guarantees
148 citations · 2011
📈 Most Prolific Year: 2011 (4 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Boston University, University of Maryland, College Park

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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