Lilin Xue
Papers
1
Total Citations
11
H-Index
1
About
Dr. Lilin Xue is a leading researcher in autonomous robotics and deep learning, with a focus on intelligent navigation systems. Her most cited work, "A Hybrid CNN-LSTM Architecture for Path Planning of Mobile Robots in Unknown Environments" (2020, 11 citations), introduces a groundbreaking end-to-end deep learning framework that integrates convolutional and recurrent neural networks. This approach eliminates the need for traditional mapping, localization, and sensor data processing steps, enabling mobile robots to navigate unfamiliar terrains with minimal human intervention. By reducing the computational overhead of map-building and manual algorithm design, Xue’s architecture significantly lowers deployment costs and enhances real-time decision-making in dynamic settings. Her contributions have advanced the field of autonomous path planning, offering a scalable solution for applications ranging from warehouse logistics to search-and-rescue operations. With a growing citation impact, Xue’s work continues to inspire innovations in hybrid deep learning models for robotics. Her research exemplifies the synergy between neural network design and practical robotic autonomy, making her a notable figure in the intersection of artificial intelligence and mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1