Yiheng Guan
Papers
1
Total Citations
4
H-Index
1
About
Yiheng Guan specializes in computer vision and robotics, with a focus on real-time tracking and control systems for competitive robotic platforms. His most-cited work, “Development of Tracking and Control System Based on Computer Vision for RoboMaster Competition Robot,” introduces a hybrid approach that fuses traditional computer vision techniques with neural networks to achieve high-speed, robust object detection and auto-aiming. The system operates at over 100 frames per second, enabling precise target engagement in dynamic, fast-paced environments. This contribution directly addresses the challenges of latency and accuracy in robotic competition settings, demonstrating practical deployment under real-world constraints. Although early in his career, Guan’s work has garnered attention within the robotics and computer vision communities, with his primary paper accumulating 4 citations as a foundation for further innovation. His research bridges the gap between classical algorithms and modern deep learning, offering a scalable solution for autonomous targeting systems. Guan’s achievements highlight the growing importance of efficient, real-time vision systems in competitive robotics and beyond, positioning him as a promising contributor to the field.
Research Focus
Key Achievements
Top Papers
- 1