Papers
15
Total Citations
132
H-Index
7
About
Than Le is a robotics researcher whose work spans motion planning, human-robot interaction, and autonomous systems. His most influential contributions include the development of "D* Lite with Reset," an improved version of the D* Lite algorithm that addresses efficiency challenges in complex environments (20 citations). Le has also made significant strides in integrating deep learning with robotics, particularly through the use of Mask R-CNN for human-robot interaction, enabling robust detection, recognition, tracking, and segmentation of human faces to guide robotic movements (19 citations). His research on search-based planning and replanning algorithms, detailed in a comprehensive chapter, has become a foundational resource for autonomous navigation (16 citations). Additionally, Le has explored forward and inverse kinematics for humanoid robotic arms (15 citations), swarm robot communication and cooperation in motion planning (14 citations), and model-based Q-learning for humanoid robots (14 citations). His work on real-time localization and tracking systems with multiple-angle views (6 citations) and digital twins for industrial applications (3 citations) further demonstrates his versatility. With over 120 total citations, Le's research continues to influence both theoretical advancements and practical implementations in robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1D* Lite with Reset: Improved Version of D* Lite for Complex Environment20 citations · 2017
- 2
- 3Search-Based Planning and Replanning in Robotics and Autonomous Systems16 citations · 2018
- 4
- 5Swarm Robots’ Communication and Cooperation in Motion Planning14 citations · 2016
- 6Model-based Q-learning for humanoid robots14 citations · 2017
- 7
- 8
- 9
- 10