Yaowen Sun
Papers
1
Total Citations
22
H-Index
1
About
Yaowen Sun is a leading researcher in the field of robotic perception and autonomous navigation, with a core focus on multi-sensor fusion for simultaneous localization and mapping (SLAM). His most influential work, "Fusion of binocular vision, 2D lidar and IMU for outdoor localization and indoor planar mapping," introduces the BVLI-SLAM framework, a pioneering scheme that integrates binocular vision, 2D lidar, and inertial measurement units to overcome the limitations of single-sensor systems. This contribution is critical for emerging applications in IoT, driverless cars, and indoor mobile robots, offering robust performance across diverse environments. With over 22 citations, this paper has quickly become a reference point for researchers tackling real-world SLAM challenges. Sun’s work stands out for its practical approach to sensor fusion, enabling reliable outdoor localization and precise indoor planar mapping. His achievements highlight a deep understanding of the hardware-software interface, positioning him as a key innovator in advancing autonomous systems. For students and researchers exploring multi-modal perception, Sun’s research provides a foundational blueprint for building more resilient and accurate robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1