Chaoquan Tan

Guilin University of Electronic Technology

Papers

Total Citations

H-Index

About

Chaoquan Tan is a researcher specializing in robotics and automated manufacturing, with a particular focus on intelligent path planning for industrial grinding applications. His work addresses critical challenges in the automation of material removal processes, especially in the repair and maintenance of drilling tools. Tan’s most cited paper, "A Path Planning Method Based on Robot Automatic Grinding of Drills" (2021), proposes a novel approach that integrates 3D scanning and point cloud data processing to guide industrial robots in precisely grinding excess material from PDC bits. By leveraging Geomagic Studio for data processing, his method enhances accuracy and efficiency in automated grinding, reducing reliance on manual labor. Although his citation count is modest, his contributions are significant in the niche field of robotic repair and manufacturing, where precision and repeatability are paramount. Tan’s work is particularly valuable for industries such as oil and gas drilling, where tool longevity directly impacts operational costs. His research represents a practical step toward fully autonomous maintenance systems, combining robotics, computer vision, and manufacturing engineering to solve real-world industrial problems.