Tien-Dung Ngo
Papers
1
Total Citations
7
H-Index
1
About
Tien-Dung Ngo is a robotics researcher whose work focuses on autonomous navigation and motion planning for mobile robots in complex, unknown environments. His most-cited paper, "Mapping and Path Planning for the Differential Drive Wheeled Mobile Robot in Unknown Indoor Environments Using the Rapidly Exploring Random Tree Method" (2022), has garnered 7 citations, showcasing his contributions to developing efficient, real-time algorithms for robots operating without prior maps. By integrating the Rapidly Exploring Random Tree (RRT) method with simultaneous localization and mapping (SLAM), Ngo addresses critical challenges in indoor robotics, such as obstacle avoidance and dynamic path optimization. His research bridges theoretical robotics with practical applications, particularly for differential drive platforms, which are widely used in service and industrial robots. Ngo’s work is notable for its emphasis on computational efficiency and adaptability, making it valuable for students and engineers developing autonomous systems. His achievements highlight a commitment to advancing robotic autonomy in unstructured settings, with potential impacts on search-and-rescue, warehouse automation, and domestic robotics.
Research Focus
Key Achievements
Top Papers
- 1