Hu Guanshan

Papers

Total Citations

H-Index

About

Hu Guanshan is a researcher specializing in autonomous robotics, intelligent control systems, and sensor fusion technologies. His work focuses on developing advanced computational methods that enable mobile robots to navigate complex, obstacle-filled environments safely and efficiently. Through the integration of fuzzy logic and neural network architectures, Hu has made meaningful contributions to the field of motion planning, addressing one of robotics' most persistent challenges: enabling machines to make real-time navigational decisions in partially structured, unpredictable spaces. His most recognized publication, "Neural Network Applications in Sensor Fusion for a Mobile Robot Motion" (2010), proposes a sophisticated technique for autonomous robot movement by combining multi-sensor data streams with neural network-driven path construction, accumulating 6 citations. Building on this foundation, his earlier work, "Neural Networks Based on Information Fusion Using for Avoiding Obstacle Robot" (2009), demonstrated practical indoor applications for wheeled autonomous robots navigating environments with arbitrarily shaped obstacles. Together, these contributions reflect a consistent research vision centered on making robotic systems smarter, safer, and more adaptive. Hu's work offers valuable foundational insights for students and researchers exploring the intersection of artificial intelligence and autonomous systems engineering.