Papers
43
Total Citations
747
H-Index
14
About
Ayan Dutta is a robotics and artificial intelligence researcher whose work spans multi-robot systems, deep reinforcement learning, and autonomous exploration. His most influential contribution, a 2023 survey on multi-agent deep reinforcement learning for multi-robot applications (161 citations), has become a key reference for researchers navigating the rapidly evolving intersection of AI and robotics. His earlier work on ModRED (75 citations), a modular self-reconfigurable robot designed for extra-terrestrial exploration, demonstrated his early interest in building adaptable, dexterous robotic systems for extreme environments. Dutta has made significant strides in multi-robot coordination, developing algorithms for informative path planning under communication and energy constraints, coalition formation for task allocation, and coverage path planning — problems of fundamental importance in real-world deployments. His work on precision agriculture (54 citations) highlights his commitment to socially impactful applications of multi-robot systems. He has also contributed to foundational distributed computing questions, including circle formation by asynchronous robots, and terrain classification using ensemble learning methods. Across more than a decade of research, Dutta has built a cohesive body of work that bridges theoretical rigor with practical robotics, making his scholarship essential reading for students and practitioners in autonomous systems and multi-agent AI.
Research Focus
Key Achievements
Top Papers
- 1Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey161 citations · 2023
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- 4Circle Formation by Asynchronous Fat Robots with Limited Visibility42 citations · 2012
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- 8Optimal Online Coverage Path Planning with Energy Constraints26 citations · 2019
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- 10Circle Formation by Asynchronous Transparent Fat Robots22 citations · 2013