Qingyang Lang
Papers
1
Total Citations
4
H-Index
1
About
Qingyang Lang is a researcher specializing in robotics perception and simultaneous localization and mapping (SLAM), with a particular focus on sensor fusion and comparative evaluation of 2D SLAM techniques. Their most notable contribution, "An Evaluation of 2D SLAM Techniques Based on Kinect and Laser Scanner" (2017), provides a rigorous benchmarking of SLAM algorithms using both low-cost RGB-D sensors and traditional laser scanners. This work has been cited 4 times, offering practical guidance for researchers and engineers selecting SLAM solutions for indoor mobile robotics. Lang’s research addresses the critical challenge of balancing accuracy, cost, and computational efficiency in autonomous navigation systems. By systematically comparing sensor modalities, they have helped advance the understanding of how sensor choice impacts SLAM performance in real-world environments. Their work is particularly valuable for students and practitioners seeking to implement robust localization systems on resource-constrained platforms. Lang’s contributions continue to inform the development of accessible, high-performance mapping solutions for service robots and autonomous vehicles.
Research Focus
Key Achievements
Top Papers
- 1An Evaluation of 2D SLAM Techniques Based on Kinect and Laser Scanner4 citations · 2017