Yanyong Zhang
University of Science and Technology of China, IMDEA Networks
Papers
9
Total Citations
80
H-Index
5
About
Yanyong Zhang is a robotics and autonomous systems researcher whose work spans LiDAR-based simultaneous localization and mapping (SLAM), multi-modal sensor fusion, and deep reinforcement learning for robot navigation. Zhang's most influential contribution, PFilter (2022, 25 citations), advances LiDAR-based SLAM by introducing persistent feature filtering to achieve fast and accurate point cloud registration under constrained computational resources — a critical challenge for mobile robots and autonomous vehicles. Building on this foundation, Zhang pioneered MM-Gaussian (2024, 16 citations), a novel LiDAR-camera multimodal fusion system leveraging 3D Gaussian representations for localization and reconstruction in unbounded outdoor scenes. Zhang also contributed the USTC FLICAR dataset (2023, 9 citations), a rich sensor fusion benchmark supporting autonomous aerial work robots. Alongside mapping research, Zhang has made meaningful strides in reinforcement learning, developing adaptive execution frameworks for robot navigation in semi-Markov models and investigating anti-jamming strategies for UAV relay systems. Zhang's broader portfolio encompasses 3D object detection, obstacle avoidance in partially observed environments, and sensor system algorithms — collectively demonstrating a versatile research vision oriented toward making autonomous systems more robust, efficient, and practically deployable.
Research Focus
Key Achievements
Top Papers
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- 5Algorithms for Sensor Systems5 citations · 2017
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- 8DRQN-based 3D Obstacle Avoidance with a Limited Field of View2 citations · 2021
- 93D Object Detection on Voxels in Spherical Coordinate System1 citations · 2021