Papers
1
Total Citations
20
H-Index
1
About
Kaikai Sun is a researcher whose work lies at the intersection of robotics, image recognition, and intelligent mining systems. His primary research focuses on developing automated solutions for coal production, particularly through the use of pick-up robots designed to separate gangue from raw coal—a critical and labor-intensive step in the mining process. Sun’s most cited paper, “An Image Recognition Approach for Coal and Gangue Used in Pick-Up Robot” (2018), with 20 citations, introduces a vision-based method that enables robots to accurately distinguish between coal and waste rock in fixed working environments. This contribution is significant because it offers a viable alternative to manual sorting, improving both efficiency and safety in mining operations. By leveraging image recognition techniques tailored to the unitary conditions of coal processing, Sun’s work advances the automation of resource extraction, reducing human exposure to hazardous conditions. His research not only addresses practical industrial challenges but also lays the groundwork for broader applications of robotics in mineral processing, making him a notable figure in the field of intelligent mining systems.
Research Focus
Key Achievements
Top Papers
- 1An Image Recognition Approach for Coal and Gangue Used in Pick-Up Robot20 citations · 2018