Max Robotics — Global Service Robot Directory + US Certification

About

Zichen Liang is a researcher specializing in 3D perception, autonomous systems, and robotic vision, with a particular focus on bridging cutting-edge sensor technologies with deep learning methodologies. His most influential work, a comprehensive survey on deep learning for LiDAR-based 3D perception (2022, 40 citations), has established itself as a valuable reference for researchers navigating the rapidly evolving landscape of autonomous driving and robotics, systematically examining both LiDAR-only and sensor-fusion approaches for environmental understanding. Liang has also made notable contributions to the emerging field of neuromorphic vision, pioneering the application of event-based sensors to robotic grasping detection. His development of dedicated event-stream datasets (2020, 29 citations) has provided the research community with critical resources for advancing this unconventional but promising sensing paradigm. Additionally, his work on globally-optimal inlier maximization for relative pose estimation addresses a challenging outlier-robustness problem in visual odometry and SLAM for mobile robots operating under planar motion constraints. Across these diverse contributions, Liang demonstrates a consistent drive to enhance robotic perception systems through innovative sensor modalities and mathematically rigorous algorithms, making his work highly relevant to researchers in autonomous vehicles, robotics, and computer vision.