I’m an undergraduate at the Gaoling School of Artificial Intelligence, Renmin University of China.

I am passionate about Visual SLAM and Multimodal Learning, and I strive to develop the next generation of efficient, robust, and intelligent systems for real-world perception, localization, and mapping.

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My work focuses on building practical and high-performance systems for autonomous agents and Visual SLAM.

• NeneBot

  • A RAG conversational AI combining FAISS semantic retrieval with pluggable LLM backends (Claude, DeepSeek, or local Ollama). Features multi-turn session memory, SSE token streaming, a modern Vue 3 immersive Galgame UI, and similarity-threshold filtering for hallucination-free character reproduction.

• LiteVO

  • End-to-end lightweight C++ monocular visual odometry combining KLT optical flow tracking and robust pose estimation. Supports real-time camera trajectory visualization, demonstrating classical multi-view geometry for spatial perception applications.

• Languages: C++17 · Python3 · Java · Go

• SLAM & Perception: ORB-SLAM3 · Feature-based & Direct VO · VIO · Loop Closure · Dynamic Map Update

• Optimization & Theory: Factor Graph · Bundle Adjustment · Lie Group/Algebra · EKF/ESKF

• Deep Learning: SuperPoint · SuperGlue · Visual Transformers (ViT)

• Libraries & Tools: Eigen · OpenCV · g2o · Ceres · ROS2 · CUDA