Shahnorbanun Sahran
Papers
6
Total Citations
40
H-Index
4
About
Shahnorbanun Sahran is a robotics researcher whose work centers on the critical challenge of enabling autonomous navigation through advanced computer vision and simultaneous localization and mapping (SLAM). Her most influential paper, “Simultaneous Localization and Mapping Trends and Humanoid Robot Linkages” (14 citations), provides a foundational survey of SLAM techniques and their application to humanoid robotics, establishing her as a key voice in this domain. Sahran has made significant contributions to robot vision, developing camera calibration methods that improve performance in degraded environments and creating video stabilization frameworks for robust localization. Her work on visual odometry trajectory estimation, using multiple descriptors to enhance VSLAM systems, directly addresses the core problem of accurate camera pose estimation for mobile robots. Beyond navigation, she has explored practical applications such as ball control techniques for robot soccer and innovative educational approaches, including teaching robot kinematics in virtual environments. Sahran’s research consistently bridges theoretical SLAM advances with real-world robotic systems, making her work essential reading for students and researchers interested in autonomous navigation, humanoid robotics, and vision-based localization.
Research Focus
Key Achievements
Top Papers
- 1Simultaneous Localization and Mapping Trends and Humanoid Robot Linkages14 citations · 2013
- 2Teaching Robot Kinematic in a Virtual Environment9 citations · 2010
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- 6Multiple Descriptors for Visual Odometry Trajectory Estimation2 citations · 2018