Papers
3
Total Citations
9
H-Index
2
About
Lingling Zhang is an emerging researcher whose work spans robotics, autonomous systems, and artificial intelligence, with a particular focus on mobile robot navigation and natural language processing. Zhang's most notable contributions lie in the development of advanced path planning and control strategies for mobile robots operating under uncertain dynamic conditions. By innovatively refining artificial potential field methods — introducing novel attractive potential functions to overcome classical limitations such as local minima — Zhang has proposed robust frameworks that enhance navigation efficiency and real-world applicability, including promising applications in health monitoring environments. These contributions, published in 2024, have already garnered early citation traction, reflecting growing community interest in intelligent robotic systems for practical domains. Zhang's earlier work demonstrates a broader interdisciplinary curiosity, extending into the robustness and reliability of AI-driven question-and-answer systems built on natural language processing — a timely inquiry given the rapid proliferation of conversational AI technologies. Collectively, Zhang's research portfolio reflects a researcher positioned at the intersection of control theory, autonomous robotics, and applied AI, contributing foundational methods that could meaningfully advance how intelligent systems navigate complex, uncertain environments in service of human wellbeing.
Research Focus
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Top Papers
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