Zhenping Dong

Xi'an University of Architecture and Technology

Papers

Total Citations

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About

Zhenping Dong is a leading researcher in construction robotics and intelligent automation, with a focus on autonomous navigation and industrial inspection systems. His work addresses critical challenges in deploying robots within unstructured, uneven environments such as construction sites and large public building refrigeration stations. Dong’s major contributions include developing an improved A* algorithm for global path planning that significantly reduces computation time and enhances efficiency for robots navigating complex terrain. This work, published in 2025, has already garnered 3 citations, reflecting its immediate relevance to the field. Additionally, he pioneered a deep learning method for automatic pointer meter reading in inspection robots, tackling low detection accuracy in refrigeration stations. This innovation, cited 2 times since 2024, advances intelligent operation and maintenance in large facilities. Dong’s research stands out for its practical impact on real-world automation challenges, bridging the gap between algorithmic theory and applied robotics. His achievements underscore a commitment to enhancing robot autonomy in demanding industrial settings, making him a notable figure in construction and facility management technologies.