Yongpeng Wang
Papers
1
Total Citations
43
H-Index
1
About
Yongpeng Wang is a leading researcher in robotic excavation and mining automation, with a primary focus on optimizing the digging performance of cable shovels—critical earth-moving equipment in open-pit mining. His most cited work, "Digging Trajectory Optimization for Cable Shovel Robotic Excavation Based on a Multi-Objective Genetic Algorithm" (2020, 43 citations), tackles the fundamental challenge of planning efficient, energy-saving digging trajectories for each operational cycle. By applying multi-objective genetic algorithms, Wang has pioneered methods that simultaneously reduce energy consumption and improve excavation productivity, directly addressing the industry's need for cost-effective and sustainable operations. His research bridges the gap between traditional heavy machinery and autonomous robotic systems, laying the groundwork for smarter, more adaptive mining equipment. Wang's contributions are particularly notable for their practical impact on the open-pit mining sector, where even incremental efficiency gains translate to significant economic and environmental benefits. His work continues to influence the development of intelligent excavation technologies, making him a key figure in the advancement of robotic mining solutions.
Research Focus
Key Achievements
Top Papers
- 1