Max Robotics — Global Service Robot Directory + US Certification

About

Lianhui Jia’s research lies at the intersection of computer vision and intelligent robotics, with a focus on deep learning for pedestrian detection and the mechanical design of construction robots. In their most cited work, a 2020 review on deep learning for occluded and multi-scale pedestrian detection (46 citations), Jia systematically analyzed challenges in autonomous driving and surveillance, providing a crucial roadmap for handling occlusion and scale variation in real-world scenes. This review has become a key reference for researchers tackling robust detection in cluttered environments. Jia also advances engineering design methodology, notably integrating TRIZ and Axiomatic Design (AD) for modular robot development, demonstrated in a 2021 paper on cutter-changing robots (20 citations). This work bridges theoretical design principles with practical application, reducing product development cycles. More recently, Jia has applied these methods to tunnel boring machine (TBM) automation, designing a shotcrete robot (2024) and a muck removal robot (2023) using D–H parameter kinematics and spatial structure analysis. These contributions directly address the need for automated, efficient tunnel construction, showcasing Jia’s ability to translate computational and design innovations into tangible engineering solutions.