Max Robotics — Global Service Robot Directory + US Certification

About

Kejing He is a researcher specializing in 3D computer vision, surface reconstruction, and robotic systems, with notable contributions to both industrial automation and surgical robotics. His work addresses some of the most technically demanding challenges in visual perception, including the reconstruction of transparent and highly reflective surfaces — problems that have long confounded conventional imaging approaches. Among his most influential contributions is a laser-scanning framework using the LTFtF method for reconstructing transparent objects (2021, 44 citations), which represents a significant advance in a notoriously difficult domain. He has also developed sophisticated stereo vision systems, including a multistep matching framework for active stereo reconstruction (2020, 23 citations) and methods for handling highly reflective surfaces through dual stereo-monocular structured light fusion. His work extends to dynamic scenes, with a spatial-temporal multiplexing approach enabling dense 3D reconstruction of moving objects — directly relevant to real-time robotic manipulation. Beyond industrial vision, He has made meaningful contributions to surgical robotics, proposing an interactive hand-eye calibration method for minimally invasive surgical instruments (2020, 32 citations) that overcomes the practical limitations of conventional calibration techniques. Collectively, his research, which has attracted over 100 citations, bridges fundamental computer vision methodology with high-impact real-world robotic applications.