About

Manh Duong Phung is a leading researcher in autonomous robotics, specializing in path planning, localization, and multi-sensor fusion for unmanned aerial vehicles (UAVs) and mobile robots. His most impactful work, "Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection" (274 citations), introduced a novel optimization algorithm that dramatically improves UAV efficiency in autonomous inspection tasks, setting a benchmark in the field. Phung has also made foundational contributions to robot localization under uncertainty, developing fuzzy neural network-based extended Kalman filters and addressing challenges like random communication delay and packet loss in networked systems. His recent work on multisensor data fusion for obstacle avoidance, combining depth cameras and LiDAR, demonstrates his commitment to reliable real-world navigation. Beyond technical innovations, Phung has advanced Internet-based robotic control and tele-guidance systems, incorporating fuzzy logic to handle network uncertainties. His research extends to socially-aware robot navigation, with ongoing work on real-time human interaction recognition from RGB-D cameras. With a career spanning foundational algorithms to cutting-edge swarm and social robotics, Phung’s work is essential reading for anyone interested in robust, intelligent autonomous systems.

Research Focus

Key Achievements

5
H-Index
9
Papers
320
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection
274 citations · 2017
📈 Most Prolific Year: 2012 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: University of Engineering and Technology Lahore, Hanoi National University of Education, Fulbright University Vietnam, Vietnam National University, Hanoi, VNU University of Science

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago