Chunshan Yang

Guilin University of Aerospace Technology

Papers

Total Citations

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About

Chunshan Yang is a researcher focused on intelligent robotics and automation, with a particular emphasis on the navigation and control of automated guided vehicles (AGVs). His work addresses critical challenges in dynamic industrial environments, where AGVs must operate safely and efficiently despite unpredictable obstacles. Yang’s most cited paper, "Study on Obstacle Avoidance of AGV based on Fuzzy Neural Network" (2019), proposes a hybrid approach combining fuzzy logic and neural networks to enhance real-time decision-making for obstacle avoidance. This contribution has garnered 4 citations, reflecting its relevance in the growing field of smart manufacturing and autonomous transport. By integrating adaptive learning with rule-based control, Yang’s research offers practical solutions for improving AGV autonomy in complex settings. His work is particularly notable for bridging theoretical AI techniques with applied robotics, making it valuable for both researchers and engineers developing next-generation industrial systems. Yang’s contributions underscore the importance of robust, intelligent navigation in the era of Industry 4.0, where AGVs are increasingly central to logistics and production.