Dongyun Lin
Papers
1
Total Citations
6
H-Index
1
About
Dongyun Lin is a researcher specializing in robotics, computer vision, and simultaneous localization and mapping (SLAM), with a particular focus on RGB-D perception systems for mobile robots. His most-cited work, "Based on Nonlinear Optimization and Keyframes Dense Mapping Method for RGB-D SLAM System" (2018), presents a complete SLAM framework that integrates visual odometry, nonlinear optimization, loop closure, and dense mapping to enable real-time camera pose estimation and point cloud reconstruction. This system addresses critical challenges in autonomous navigation by combining keyframe selection with optimization techniques to improve mapping accuracy and computational efficiency. With 6 citations, this foundational paper has contributed to advancing dense mapping methods in SLAM research. Lin’s work is notable for its practical approach to building robust, real-time mapping systems that can operate in complex indoor environments, making it valuable for applications in robotics, augmented reality, and autonomous exploration. His research continues to impact the development of efficient, optimization-driven SLAM pipelines.
Research Focus
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Top Papers
- 1