Max Robotics — Global Service Robot Directory + US Certification

About

Chunran Zheng is a robotics and autonomous systems researcher whose work centers on multi-sensor fusion, Simultaneous Localization and Mapping (SLAM), and real-time state estimation for robotic platforms. He is best known for developing the FAST-LIVO series — tightly coupled LiDAR-Inertial-Visual Odometry systems that fuse IMU, LiDAR, and camera data through efficient error-state iterated Kalman filtering to deliver fast, accurate, and robust pose estimation. The original FAST-LIVO (2022) has garnered 195 citations, while its successor, FAST-LIVO2 (2024), has already accumulated 106, underscoring the sustained impact of this line of work on the robotics community. Beyond odometry, Zheng has pushed into novel scene representation, contributing LIV-GaussMap and GS-LIVO, which integrate 3D Gaussian splatting with multi-sensor fusion for high-fidelity real-time mapping — a frontier bridging classical SLAM and neural rendering. His MARS-LVIG dataset (41 citations) further reflects a commitment to community infrastructure, providing a rigorous multi-sensor aerial benchmark for LiDAR-visual-inertial-GNSS research. More recently, he has explored adaptive multi-robot target tracking under adversarial conditions. Across his portfolio, Zheng has established himself as a significant contributor to the next generation of intelligent, perception-capable robotic systems.