Max Robotics — Global Service Robot Directory + US Certification

About

Changyun Miao is a leading researcher in intelligent mining robotics, specializing in computer vision, deep learning, and automated control systems for coal preparation and conveyor safety. His most impactful work focuses on developing robust detection and tracking algorithms for gangue (waste rock) and foreign objects in coal, directly addressing critical challenges in the mining industry. Miao’s research has produced highly cited innovations, including an improved YOLOv7 and DeepSORT framework for real-time foreign object tracking (39 citations) and a deep learning-based method for belt conveyor deviation detection using inspection robots (35 citations). He further advanced gangue selection robotics with an enhanced YOLOv7 network for accurate gangue and foreign matter detection (15 citations) and pioneered intelligent trajectory control for robotic manipulators using an improved DQN reinforcement learning model (3 citations). Collectively, his work has garnered over 90 citations, demonstrating significant impact in automating hazardous and labor-intensive mining tasks. Miao’s contributions are pivotal to the development of safer, more efficient coal processing systems, positioning him as a key innovator at the intersection of robotics, deep learning, and industrial automation.