Renyin Cheng

Xi'an University of Architecture and Technology

Papers

Total Citations

H-Index

About

Renyin Cheng is a researcher focused on intelligent robotics and autonomous navigation, with a particular emphasis on path planning for specialized inspection environments. Their most-cited work, "Global path planning for airport energy station inspection robots based on improved grey wolf optimization algorithm" (2023), addresses a critical challenge in industrial robotics: navigating complex, equipment-dense spaces where traditional algorithms fall short. By enhancing the grey wolf optimization algorithm, Cheng developed a solution that enables inspection robots to efficiently traverse narrow corridors and crowded mechanical areas in airport energy stations—environments that demand both precision and safety. This contribution has already garnered attention, with 5 citations in a short period, signaling its relevance to both robotics and energy infrastructure fields. Cheng's work bridges the gap between theoretical optimization methods and real-world industrial applications, offering practical advancements for autonomous systems in high-stakes settings. Their research not only improves operational efficiency but also reduces human risk in hazardous inspection tasks, marking Cheng as an emerging voice in applied robotics and intelligent control systems.