Manas Ranjan Kabat
Papers
11
Total Citations
126
H-Index
6
About
Manas Ranjan Kabat is a leading researcher in multi-robot systems, specializing in cooperative navigation, path planning, and swarm intelligence. His work focuses on developing novel algorithms that enable multiple robots to work together efficiently in complex, dynamic environments—from carrying objects cooperatively to navigating cluttered spaces without collision. Kabat has pioneered the application of hybrid metaheuristic techniques, such as combining Improved Q-learning with Democratic Robotics PSO and fusing Intelligent Water Drops with Differential Evolution, to solve real-world coordination problems. His research has practical implications, including a notable 2021 study on using multi-robot cooperation and Q-learning to assist in preventing the spread of COVID-19 among affected patients. With over 120 citations across his most influential papers, Kabat’s contributions are recognized for their innovation in optimizing robot teamwork. His work on trust-based navigation control and twin-robot cooperation using improved Q-learning has advanced the field’s understanding of how robots can avoid deadlocks and execute tasks with minimal computational overhead.
Research Focus
Key Achievements
Top Papers
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- 5A Pragmatic Review of QoS Optimisations in IoT Driven Networks13 citations · 2024
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- 9Twin Robot Cooperation in Multi-Robot Environment: An Applied Q-learning3 citations · 2019
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