Kuan Wei Wu
Papers
1
Total Citations
23
H-Index
1
About
Kuan Wei Wu is a robotics and computer vision researcher whose work centers on real-time perception systems, with a particular focus on simultaneous localization and mapping (SLAM) and sensor calibration. His most influential contribution is a novel SLAM-based approach to self-calibrating binocular stereo vision rigs, eliminating the need for manual, off-line calibration with specific targets. This breakthrough, published in 2020 and earning 23 citations, enables autonomous calibration during operation, significantly advancing the practicality of stereo vision in dynamic environments like field robotics and autonomous navigation. By integrating SLAM principles directly into the calibration process, Wu has addressed a critical bottleneck in deploying stereo systems for real-world applications. His work demonstrates a sophisticated understanding of the interplay between localization, mapping, and sensor geometry, positioning him as a rising innovator in the development of more autonomous and self-sufficient robotic perception systems.
Research Focus
Key Achievements
Top Papers
- 1SLAM-Based Self-Calibration of a Binocular Stereo Vision Rig in Real-Time23 citations · 2020