Papers
1
Total Citations
4
H-Index
1
About
Sun Daqing is a researcher whose work sits at the intersection of robotics, computer vision, and multi-sensor fusion. His primary research focuses on enhancing autonomous systems’ perception capabilities, particularly through the integration of visual and LiDAR data for robust object detection and localization. His most cited work, "A Novel Object Detection and Localization Approach via Combining Vision with Lidar Sensor" (2021), addresses a critical challenge in robotics: maintaining accurate object awareness during movement when global visual information is limited. Daqing proposes an innovative two-component vision-based scheme, featuring a lightweight convolutional neural network (CNN) designed for real-time performance. This contribution is vital for applications in autonomous navigation and mobile robotics, where computational efficiency is paramount. With 4 citations, this paper has already begun to influence the field, demonstrating its relevance to peers tackling similar sensor fusion problems. Daqing’s work stands out for its practical, deployable approach, bridging the gap between theoretical computer vision and real-world robotic constraints. His research continues to push the boundaries of how machines perceive and interact with dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1