Cheng‐Fu Yang

National University of Kaohsiung, Chaoyang University of Technology

Papers

Total Citations

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About

Cheng-Fu Yang is a researcher advancing the frontiers of autonomous navigation and robotic control. His work primarily focuses on path planning, simultaneous localization and mapping (SLAM), and robust adaptive control for robotic systems. Yang’s most notable contribution is the development of **LLM-A***, a novel framework that integrates large language models with incremental heuristic search to enhance path planning efficiency and adaptability. This work, published in 2024, has already garnered 23 citations, signaling its significant impact on the field. Additionally, Yang proposed a composite tracking control scheme for robot manipulators that combines adaptive friction estimation with robust control, addressing challenges of unknown friction and system uncertainty. He also advanced SLAM technology through an improved cubature Kalman filter algorithm (ICKF-SLAM), which enhances precision and stability in mobile robot localization. With a citation count exceeding 34 across his top papers, Yang’s research bridges classical robotics algorithms with modern AI, offering practical solutions for autonomous systems. His work is essential reading for students and researchers interested in intelligent robotics, control theory, and AI-driven navigation.