Szu‐Hong Wang

National Yunlin University of Science and Technology

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About

Szu-Hong Wang is a robotics researcher whose work focuses on making autonomous systems more intelligent, affordable, and practical for real-world applications. His primary research areas include computer vision, sensor fusion, and deep learning for robotic navigation and control. Wang’s most influential contribution is a real-time monocular vision-based obstacle detection system, which replaces expensive laser or dual-lens sensors with a single wide-angle camera—significantly reducing hardware costs while maintaining reliable performance (11 citations). He further advanced robot autonomy through an intelligent multi-sensor navigation system that integrates laser range finders, electronic compasses, and cameras for remote monitoring and control (7 citations). Demonstrating creative problem-solving, Wang also developed a smart leaf-blowing robot that uses a deep learning convolutional neural network to autonomously clear fallen leaves, addressing a common but overlooked urban maintenance challenge (6 citations). His work bridges the gap between cutting-edge AI and cost-effective robotics, making autonomous navigation more accessible for service and domestic robots. Wang’s research continues to push the boundaries of how robots perceive and interact with their environments.