Max Robotics — Global Service Robot Directory + US Certification

About

Yunge Cui is a robotics and computer vision researcher whose work centers on 3D LiDAR perception, feature extraction, and autonomous navigation. Cui’s most impactful contribution is **LinK3D**, a novel linear keypoints representation for 3D LiDAR point clouds, which addresses a fundamental challenge in robotic vision: reliable 3D feature extraction and matching. With over 66 combined citations across two versions (2022 and 2024), LinK3D has become a recognized approach for enabling robust object detection, recognition, and registration in unstructured environments. Building on this, Cui developed an **Optimized RANSAC** method for 3D LiDAR feature matching, improving the accuracy of correspondence estimation—a critical step for tasks like SLAM and localization. Most recently, Cui has applied these perception advances to **AI-enabled autonomous mobile robot navigation in construction**, demonstrating intelligent obstacle-aware path planning in dynamic, cluttered sites. This work bridges the gap between foundational 3D vision algorithms and real-world industrial deployment. By systematically advancing from low-level point cloud matching to high-level navigation autonomy, Yunge Cui is shaping the future of field robotics in challenging, unstructured environments.