Yanbiao Sun

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About

Yanbiao Sun is a leading researcher at the intersection of robotics, computer vision, and precision measurement. His work focuses on two critical pillars for autonomous systems: ensuring sensor reliability and advancing 3D spatial understanding. Sun’s foundational contribution, “Dynamic Validation of Calibration Accuracy and Structural Robustness of a Multi-Sensor Mobile Robot” (2024, 6 citations), addresses a vital gap in robotics—providing a systematic method to verify the long-term health and calibration integrity of complex multi-sensor platforms, a prerequisite for safe autonomous operation. Pushing the boundaries of perception, his recent work “SE(3)-Equivariance Learning for Category-Level Object Pose Estimation” (2025, 1 citation) introduces a mathematically principled approach to 6D pose and size regression from point clouds. By embedding SE(3) equivariance directly into the learning architecture, Sun overcomes the brittleness of traditional regression methods, enabling robots to robustly estimate object poses even under significant viewpoint changes—a breakthrough for vision-based robotic manipulation and measurement. This work bridges theoretical geometry and practical robotics, promising to enhance the reliability of automated systems in unstructured environments. Sun’s research is pivotal for students and engineers developing next-generation autonomous robots that must perceive and interact with the world with both precision and resilience.