Teng-Wen Chang

National Yunlin University of Science and Technology

Papers

Total Citations

H-Index

About

Teng-Wen Chang is a researcher at the forefront of robotics and human-computer interaction, with key contributions in autonomous navigation and interactive fabrication. His work on "Fast Obstacle Detection Using 3D-to-2D LiDAR Point Cloud Segmentation for Collision-free Path Planning" (2020, 8 citations) addresses a critical limitation in computer vision for robotics: the sensitivity of color-based algorithms to lighting and surface reflectance. By leveraging LiDAR data and the Oren-Nayar reflectance model, Chang developed a robust method for real-time obstacle detection that works reliably across diverse materials and illumination conditions—a significant advance for autonomous systems operating in unstructured environments. In parallel, his research on "Developing an Interactive Fabrication Process of Maker Based on 'Seeing-Moving-Seeing' Model" (2019, 6 citations) explores how designers and makers can intuitively interact with digital fabrication tools, bridging the gap between physical craftsmanship and computational design. This work has implications for accessible manufacturing and creative prototyping. Though early in his career, Chang's dual focus on practical robotic perception and human-centered making demonstrates a commitment to technologies that are both intelligent and usable.