Papers
13
Total Citations
69
H-Index
4
About
Dr. Amar Nath is a leading researcher in multi-robot systems and distributed artificial intelligence, with a focus on cooperative autonomy in dynamic, real-world environments. His work addresses critical challenges in urban search and rescue, where his most-cited paper (23 citations) introduces a distributed approach for multi-robot road clearance. Dr. Nath has made foundational contributions to autonomous cooperative transportation, developing optimal coalition formation algorithms that enable robots to dynamically team up for complex tasks without centralized control. His research extends to formal verification, where he uses TLA+ and BPMN to mathematically prove the correctness of team formation and task execution protocols—a rigorous approach that ensures reliability in safety-critical applications. With over 65 total citations, his impact spans from foundational theory to applied systems, including recent work on AI-driven IoRT solutions for precision agriculture. Notably, his 2023 paper on formal specification of team formation protocols represents a significant step toward verifiable, trustworthy multi-robot coordination. For students and researchers, Dr. Nath’s work offers a compelling blueprint for building scalable, provably correct distributed robotic systems that can operate effectively in unpredictable environments.
Research Focus
Key Achievements
Top Papers
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- 3An Approach for Task Execution in Dynamic Multirobot Environment9 citations · 2018
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- 5Formal Verification of a Distributed Algorithm for Task Execution3 citations · 2020
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- 7Multi-agent Q-learning Based Navigation in an Unknown Environment3 citations · 2022
- 8Distributed Framework for Task Execution with Quantitative Skills2 citations · 2021
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