Papers
14
Total Citations
162
H-Index
7
About
Le Duc Hanh is a prominent robotics and computer vision researcher whose work sits at the intersection of intelligent automation, visual servoing, and autonomous robot systems. With a career spanning over a decade, Hanh has made substantial contributions to the development of vision-guided robotic manipulation, accumulating more than 140 citations across his most impactful publications. His most celebrated work includes the design of a dual robot arm classification and sorting system using machine vision (2022, 33 citations) and a comprehensive review of visual servoing control strategies (2023, 32 citations), which has quickly become a key reference for researchers entering the field. His development of a decoupled control law for image-based visual servoing (2022, 20 citations) represents a meaningful theoretical advancement in robot manipulator control. Hanh's research extends to mobile robotics, particularly reinforcement learning-based obstacle avoidance in dynamic environments (2023, 16 citations), as well as practical industrial applications including bin picking, sealant dispensing, and even ping-pong ball trajectory prediction. His early work combining stereo vision with fuzzy controllers for autonomous grasping (2012) demonstrates a long-standing commitment to bridging advanced control theory with real-world robotic performance.
Research Focus
Key Achievements
Top Papers
- 1
- 2A review and performance comparison of visual servoing controls32 citations · 2023
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- 6Real-time Measurement and Prediction of Ball Trajectory for Ping-pong Robot11 citations · 2020
- 7
- 8Computer Vision for Industrial Robot in Planar Bin Picking Application7 citations · 2020
- 9Catching algorithm for 2D robot manipulator using PD controller6 citations · 2009
- 10Planar Object Recognition For Bin Picking Application5 citations · 2018