Papers
10
Total Citations
118
H-Index
5
About
Ruiqing Jia is a robotics researcher whose work spans industrial automation, computer vision, reinforcement learning-based motion planning, and robotics education. With a career rooted in practical and pedagogical applications of robotic systems, Jia has made notable contributions to intelligent coal and gangue separation—a critical challenge in China's coal-dominant energy sector. His 2021 paper on computer vision-based coal and gangue separation robots has garnered 45 citations, establishing him as a leading voice in mining automation. Complementing this, his simulation-based separation system built on CoppeliaSim further advances intelligent coal mine applications. Jia has also shaped how robotics is taught at the university level. His 2019 paper on robot kinematics education using MATLAB and V-REP (24 citations) and earlier work on virtual robotics laboratories demonstrate a sustained commitment to innovative STEM pedagogy. In motion planning, he has explored both residual and curriculum reinforcement learning strategies to improve training efficiency for robotic arms. His early work on mine-rescue robots and binocular vision systems reflects a long-standing interest in hazardous-environment robotics. Across more than 15 years of research, Jia's interdisciplinary contributions bridge industrial robotics, machine learning, and engineering education.
Research Focus
Key Achievements
Top Papers
- 1Coal and Gangue Separating Robot System Based on Computer Vision45 citations · 2021
- 2
- 3Robotic Arm Motion Planning Based on Residual Reinforcement Learning17 citations · 2021
- 4Robotic Arm Motion Planning Based on Curriculum Reinforcement Learning9 citations · 2021
- 5
- 6Virtual Experiments Design for Robotics Based on V-REP5 citations · 2018
- 7
- 8Mirobot: A Low-Cost 6-DOF Educational Desktop Robot2 citations · 2021
- 9Design and analysis of missing miner searching robot2 citations · 2005
- 10