Yiyang Zhou
Papers
2
Total Citations
25
H-Index
2
About
Yiyang Zhou is a robotics researcher specializing in sensor fusion, calibration, and autonomous perception systems. His work focuses on integrating complementary sensing modalities—particularly LIDAR and cameras—to enhance robotic perception in complex environments. Zhou’s most cited paper, "SST-Calib: Simultaneous Spatial-Temporal Parameter Calibration between LIDAR and Camera" (2022, 17 citations), addresses a critical challenge in autonomous driving: precisely aligning LIDAR depth data with camera imagery over both space and time. This calibration framework improves the reliability of sensor fusion, enabling more accurate object detection and scene understanding. His earlier work, "Visual Robotic Object Grasping Through Combining RGB-D Data and 3D Meshes" (2016, 8 citations), demonstrates his foundational contributions to robotic manipulation by fusing visual and geometric data for robust grasping. Zhou’s research has direct applications in autonomous vehicles, service robotics, and industrial automation, where robust multi-sensor systems are essential. His work on SST-Calib is particularly notable for addressing the often-overlooked temporal misalignment between sensors, a key bottleneck in real-world deployment. With growing citation impact, Zhou is establishing himself as a rising expert in calibration and sensor fusion for intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2