Zongjian Mo

Guilin University of Electronic Technology

Papers

Total Citations

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About

Zongjian Mo is a robotics researcher whose work focuses on advancing robotic systems for inspection, repair, and autonomous navigation. His primary research areas include pipeline inspection robotics, industrial robot calibration, and simultaneous localization and mapping (SLAM) algorithms. Mo’s most notable contribution is the development of a novel wheeled-leg pipeline robot designed for operation in small, pre-buried pipes, addressing the critical challenge of detecting corrosion and crack defects in inaccessible infrastructure. His kinematic analysis of this robot navigating curved pipes (2024, 7 citations) provides foundational insights for compact, agile inspection platforms. In industrial applications, Mo pioneered a dual-robot system for laser cladding repair of high-value polycrystalline diamond compact (PDC) drill bits, integrating 3D hand–eye calibration and structured light scanning (2025, 4 citations)—a significant advancement for automated remanufacturing. He also developed a ROS-Gazebo simulation-based evaluation method for SLAM algorithms (2022), enabling researchers to benchmark performance with known ground-truth trajectories. With a growing citation footprint and work spanning from theoretical simulation to practical industrial repair, Mo’s research is shaping the future of autonomous robotics in confined and hazardous environments.