Md Mohiuddin Khan
Papers
3
Total Citations
31
H-Index
3
About
Md Mohiuddin Khan is a researcher at the forefront of intelligent swarm robotics, focusing on the intersection of collective behavior, autonomous control, and environmental sensing. His work has pioneered the use of actor-critic deep reinforcement learning to automatically tune the motion of robot swarms, enabling them to adapt their collective dynamics in real time without human intervention. This breakthrough, detailed in his most-cited paper (19 citations), addresses a core challenge in swarm robotics: achieving robust, scalable coordination in unstructured environments. Khan has also advanced the field by developing methods for swarms to autonomously recognize their own collective behaviors—a critical step toward self-aware robotic systems—and by formulating swarm tuning strategies for environmental sensing tasks, such as coverage problems, where robots must efficiently monitor or map areas. With over 30 total citations across his key works, his contributions are shaping how autonomous swarms can be deployed for real-world applications like disaster response, environmental monitoring, and exploration. His research stands out for its practical focus on making swarm intelligence both trainable and interpretable.
Research Focus
Key Achievements
Top Papers
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- 3Autonomous Recognition of Collective Behaviour in Robot Swarms5 citations · 2020