Thang Viet Tran
Papers
1
Total Citations
2
H-Index
1
About
Thang Viet Tran is a researcher specializing in robotics, computer vision, and autonomous manipulation, with a particular focus on integrating depth-sensing technologies into industrial and service robot systems. His work centers on developing practical methods for object localization and grasping, addressing key challenges in pick-and-place automation. Tran’s most cited paper, "A Method for Localizing and Grasping Objects in a Picking Robot System Using Kinect Camera" (2021), introduces a novel approach that leverages low-cost RGB-D sensors to enable robots to accurately detect and manipulate objects in cluttered environments. This contribution has garnered attention for its potential to make robotic grasping more accessible and efficient, with 2 citations to date. While his citation count is modest, the work reflects a growing interest in affordable, sensor-driven automation solutions. Tran’s research bridges the gap between theoretical computer vision algorithms and real-world robotic applications, offering a pathway for students and engineers to explore cost-effective automation. His ongoing efforts continue to advance the field of intelligent robotics, particularly in the context of warehouse logistics and manufacturing.
Research Focus
Key Achievements
Top Papers
- 1