Papers
7
Total Citations
32
H-Index
3
About
Thanh Nguyen Canh is an emerging robotics researcher whose work spans autonomous navigation, human-robot interaction, and robot vision systems. With a growing body of publications accumulating over 30 citations, his research addresses some of the most pressing challenges in modern robotics, particularly enabling machines to perceive, reason, and move safely in complex real-world environments. His foundational contributions lie in sensor fusion and perception, most notably his multisensor data fusion framework combining depth cameras and LiDAR for reliable obstacle avoidance. This work exemplifies his broader commitment to robust robot perception, further demonstrated through object-oriented semantic mapping for UAV navigation in search-and-rescue scenarios. Thanh has also made significant strides in social robot navigation, proposing integrated motion prediction and trajectory planning systems that allow mobile robots to operate safely alongside humans. Beyond navigation, his research extends to industrial robot vision, where his M-Calib framework advances monocular 3D object localization using deep learning, and to underwater robotics, addressing depth estimation challenges in visually degraded environments. His 2024 work on designing and fabricating dual-arm service robots highlights his versatility, bridging theoretical algorithms with practical hardware development. Thanh's diverse yet cohesive research portfolio positions him as a promising voice in the next generation of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1Multisensor Data Fusion for Reliable Obstacle Avoidance8 citations · 2022
- 2
- 3Object-Oriented Semantic Mapping for Reliable UAVs Navigation7 citations · 2023
- 4
- 5
- 6
- 7