Papers
16
Total Citations
382
H-Index
6
About
Pavel Surynek is a leading researcher in multi-robot path planning (MRPP) and cooperative path-finding, with a focus on the computational foundations of coordinating multiple mobile robots. His seminal 2010 paper, "An Optimization Variant of Multi-Robot Path Planning Is Intractable" (167 citations), established key complexity results for optimization in this domain. Surynek’s work often employs elegant abstractions, modeling robot environments as undirected graphs and leveraging the classic "pebble motion on graphs" framework to derive efficient solutions. He has made significant contributions to understanding solvability in bi-connected graphs (120 citations) and has pioneered the use of propositional satisfiability (SAT) and Satisfiability Modulo Theory (SMT) techniques for optimal and suboptimal path planning. His research addresses both theoretical intractability and practical algorithm design, including redundancy elimination in parallel coordination and shorter solution generation for structured environments like theta-like graphs. With over 350 total citations, Surynek’s impact is evident in his consistent exploration of hard combinatorial problems and their algorithmic solutions. His recent work extends to accessible robotics education, including a 3D-printed robotic arm for teaching Industry 4.0, demonstrating a commitment to bridging theory and practice.
Research Focus
Key Achievements
Top Papers
- 1An Optimization Variant of Multi-Robot Path Planning Is Intractable167 citations · 2010
- 2A novel approach to path planning for multiple robots in bi-connected graphs120 citations · 2009
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- 4Multi-Robot Path Planning15 citations · 2011
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