Yaqian Shi
Papers
1
Total Citations
5
H-Index
1
About
Yaqian Shi is a researcher whose work lies at the intersection of computer vision, robotics, and autonomous navigation in unstructured environments. Her most cited contribution, "A High-Precision Vision-Based Mobile Robot Slope Detection Method in Unknown Environment" (2018), addresses a critical challenge in field robotics: enabling mobile robots to accurately perceive and navigate slopes without prior environmental knowledge. By developing a vision-based method that extracts slope geometry from RGB imagery, Shi's work enhances robot autonomy in complex terrains where traditional sensors may fail. Though her citation count is modest, her research is foundational for applications in search-and-rescue, planetary exploration, and agricultural robotics. Shi’s focus on high-precision, low-cost perception systems demonstrates a commitment to practical, deployable solutions. Her contributions are particularly valuable for students and engineers working on real-world robotic navigation, offering a robust approach to one of the most difficult problems in mobile robotics: safe traversal of unknown, uneven ground.
Research Focus
Key Achievements
Top Papers
- 1