Jingsen Jin

Guilin University of Electronic Technology

Papers

Total Citations

H-Index

About

Jingsen Jin is a researcher focused on advancing industrial robotics for automated repair and manufacturing, with key contributions in laser cladding, path planning, and multi-robot calibration. His work centers on solving practical challenges in restoring worn industrial drill bits, particularly through the integration of 3D scanning and robotic automation. Jin’s most cited paper, “Smooth path generation method of laser cladding bit repair robot based on 3D automatic measurement of wear surface point cloud” (2021, 4 citations), introduces a novel method for generating cladding paths on irregular curved surfaces, addressing a critical bottleneck in laser cladding repair. In “Calibration of Dual Industrial Robot System Based on Hand-Eye Calibration Algorithm” (2021, 4 citations), he tackles low calibration accuracy in dual-robot systems to improve cladding efficiency and quality. Additionally, his work on “A Path Planning Method Based on Robot Automatic Grinding of Drills” (2021, 2 citations) proposes automated grinding path planning using point cloud data from 3D scans. Though early in his career, Jin’s research demonstrates a clear impact on automating complex repair processes, offering practical solutions for industrial applications. His achievements highlight a promising trajectory in robotics and manufacturing automation.