Qingbao Bao
Papers
1
Total Citations
9
H-Index
1
About
Qingbao Bao is a leading researcher in intelligent mining equipment and mechatronic systems, with a focus on the coordinated control of hydraulic supports and scraper conveyors—critical components in fully mechanized coal mining. His work addresses the complex path planning of hydraulic support pushing mechanisms, which serve as floating connections essential for synchronized movement. In his highly cited 2021 paper, Bao pioneered a method combining extreme learning machines (ELM) with Descartes path planning, achieving efficient, real-time trajectory optimization that enhances automation and safety in underground mining. This contribution has garnered 9 citations, reflecting its practical impact on advancing smart mining technologies. Bao’s research bridges computational intelligence and mechanical engineering, offering scalable solutions for autonomous mining operations. His achievements underscore a commitment to improving operational efficiency and reducing human risk in hazardous environments, positioning him as a key innovator in the field of mining robotics and intelligent equipment control.
Research Focus
Key Achievements
Top Papers
- 1