Pingan Peng
Papers
2
Total Citations
8
H-Index
2
About
Pingan Peng is a leading researcher in autonomous systems for mining environments, with a focus on robotics, deep learning, and intelligent vehicle control. His work addresses critical challenges in underground and industrial automation, particularly through the development of unmanned driving systems for load-haul-dump vehicles. Peng’s 2022 paper on modeling and simulation of such systems, using Gazebo/ROS, provides a foundational framework for autonomous navigation in hazardous underground settings, earning 4 citations. In 2024, he advanced the field with MAMRS, a mining automatic meter reading system that integrates quadruped robots with improved deep learning algorithms. This innovation replaces manual inspection in power distribution rooms, enhancing safety and efficiency, and has also garnered 4 citations. Peng’s contributions are pivotal in transforming traditional mining operations into automated, data-driven processes. His work not only reduces human risk but also improves operational timeliness, marking him as a key figure in the intersection of robotics and mining engineering.
Research Focus
Key Achievements
Top Papers
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