Yan Tan
Papers
2
Total Citations
25
H-Index
2
About
Yan Tan is a researcher whose work spans robotics and medical case studies, demonstrating versatility across engineering and clinical domains. Their primary research focus lies in mobile robotics, particularly path planning optimization. Tan’s most significant contribution is the development of the Evolutionary Artificial Potential Fields (EAPF) approach, a novel method that enhances traditional Artificial Potential Field theory by enabling robots to escape local minima during navigation. This work, published in 2013 and cited 22 times, provides a practical solution to a longstanding challenge in autonomous robot movement, making it a valuable reference for researchers in robotics and artificial intelligence. In addition to their engineering contributions, Tan has co-authored a rare medical case report on primitive neuroectodermal tumor (PNET) of the prostate in a 58-year-old man (2022), highlighting the importance of multidisciplinary collaboration. This case study, though with fewer citations, underscores Tan’s ability to contribute to specialized clinical literature. Overall, Yan Tan’s work bridges theoretical robotics and real-world medical reporting, offering insights that benefit both fields and inspiring further innovation in autonomous systems and rare disease documentation.
Research Focus
Key Achievements
Top Papers
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- 2