Cheng-Yu Peng

National Chin-Yi University of Technology

Papers

Total Citations

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About

Cheng-Yu Peng is a robotics and automation researcher whose work bridges the gap between intelligent perception and real-world manipulation. His primary research areas include simultaneous localization and mapping (SLAM), automated optical inspection (AOI), and robotic vision systems. Peng’s most cited work, “Outdoor Positioning Based on ROS LiDAR Navigation Compared with RTK GPS Accuracy” (2023, 3 citations), advances autonomous navigation by implementing particle-filtering algorithms—gmapping and adaptive Monte Carlo localization (AMCL)—within the ROS 1 framework. This study provides a practical comparison between LiDAR-based SLAM and high-precision RTK GPS, offering valuable insights for outdoor mobile robot deployment. In “Automatic Feeding System with High Accuracy Intelligent Product Defection Function” (2023, 3 citations), Peng explores the integration of AOI with automation to achieve rapid, labor-free defect detection. His earlier work, “Robotic Arm Combined with the Visual Images in a Transparent Object Recognition” (2020, 2 citations), tackles the challenging problem of transparent object recognition using a robot-mounted camera and LabView integration for pick-and-place tasks. Though early in his career, Peng’s contributions demonstrate a clear trajectory toward practical, sensor-driven automation solutions that enhance both navigation accuracy and manufacturing intelligence.