Zhentao Huang
Papers
1
Total Citations
14
H-Index
1
About
Zhentao Huang is a researcher specializing in robotics perception, computer vision, and sensor calibration, with a particular focus on active vision systems. His work addresses the critical challenge of hand-eye calibration—the process of determining the geometric relationship between a robot's arm and its camera—by introducing an innovative, accuracy-driven approach. In his most-cited paper, "Active hand-eye calibration via online accuracy-driven next-best-view selection" (2022), Huang proposes a method that actively selects the optimal camera viewpoint during calibration, significantly improving precision and efficiency over traditional static techniques. This contribution has garnered 14 citations, reflecting its impact on the robotics community. Huang's research is notable for its practical application in autonomous systems, where real-time calibration is essential for tasks like object manipulation and navigation. By integrating online decision-making with calibration, his work paves the way for more adaptive and reliable robotic systems. For students and researchers exploring sensor fusion or robot autonomy, Huang's studies offer a compelling example of how active perception can enhance system performance in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1