Papers
11
Total Citations
193
H-Index
7
About
John Vian is a prominent researcher specializing in multi-robot systems, autonomous decision-making, and decentralized planning under uncertainty. His work sits at the intersection of robotics, artificial intelligence, and cyber-physical systems, with a particular focus on enabling coordinated behavior among teams of autonomous vehicles operating in complex, real-world environments. Vian's most influential contribution — his 2017 paper on decentralized control of multi-robot Partially Observable Markov Decision Processes (Dec-POMDPs) using belief space macro-actions, garnering 60 citations — advanced the field by tackling the formidable challenge of multi-robot coordination in continuous spaces with incomplete information. Complementing this, his probabilistic and graph-based approaches to Dec-POMDPs further demonstrated his commitment to scalable, computationally tractable solutions for real-world deployment. Beyond theoretical advances, Vian has made notable practical contributions through testbed development, including the Vehicle Swarm Rapid Prototyping Testbed and the Measurable Augmented Reality platform for cyber-physical systems prototyping, bridging the gap between algorithmic research and hardware implementation. His work on adaptive task allocation, heterogeneous multiagent learning for forest fire management, and Bayesian noise inference for robust object classification further illustrates the breadth and applicability of his research. Collectively accumulating nearly 190 citations, Vian's portfolio represents meaningful, sustained contributions to autonomous multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Vehicle Swarm Rapid Prototyping Testbed30 citations · 2009
- 3Adaptive task allocation for search area coverage23 citations · 2009
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- 7MAR-CPS: Measurable Augmented Reality for Prototyping Cyber-Physical Systems12 citations · 2015
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