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About

Diptendu Sinha Roy is a robotics and artificial intelligence researcher whose work centers on the challenging problem of multi-robot navigation, motion planning, and coordinated autonomy in shared environments. His research addresses one of the field's most complex dilemmas: enabling individual robots to pursue independent goals without compromising collective system performance. Roy's most influential contribution, "A Novel Hybrid Neural Network-Based Multirobot Path Planning With Motion Coordination" (2020), has garnered 36 citations and demonstrates his innovative application of neural networks to synchronize robot motion across dynamic workspaces. His broader body of work integrates diverse intelligent methodologies — including genetic algorithm-fuzzy systems, potential field methods, and game-theoretic strategies — to develop robust coordination frameworks for robotic swarms. Papers such as "Game-Theoretic Strategic Coordination and Navigation of Multiple Wheeled Robots" (2021) reflect his forward-thinking approach to modeling robot decision-making as a strategic negotiation problem. Spanning publications from 2018 to 2021 with a cumulative citation count exceeding 75, Roy's research has established meaningful benchmarks in cooperative robotics. His work is particularly valuable for students and engineers exploring scalable, collision-free navigation solutions for real-world multi-agent autonomous systems.