Hendra Suratno
Papers
1
Total Citations
6
H-Index
1
About
Hendra Suratno is a researcher in robotics and computer vision, with a focus on visual odometry and autonomous navigation. His most influential work, "Visual odometry using RGB-D camera on ceiling vision" (2012), introduces a novel algorithm that leverages ceiling-mounted features for robot localization. The key contribution is a principal direction detection method that significantly reduces error accumulation—a persistent challenge in traditional visual odometry. This approach enables more accurate and stable pose estimation, particularly in indoor environments where ceiling features provide reliable visual cues. With 6 citations, this paper has laid groundwork for further research in vision-based navigation systems. Suratno’s work is notable for its practical application in mobile robotics, offering a cost-effective solution for real-time localization without reliance on external infrastructure. His contributions are valuable for students and researchers exploring RGB-D sensing, SLAM, and autonomous systems, demonstrating how clever algorithmic design can overcome fundamental limitations in visual odometry.
Research Focus
Key Achievements
Top Papers
- 1Visual odometry using RGB-D camera on ceiling vision6 citations · 2012