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About

Wuyang Xue is a leading researcher in autonomous navigation, specializing in the integration of multi-sensor fusion, simultaneous localization and mapping (SLAM), and intelligent path planning for mobile robots and autonomous vehicles. His most impactful contribution is the development of a graph-based adaptive fusion system for GNSS and visual-inertial odometry (VIO), which ensures consistent global positioning even under intermittent GNSS-degraded environments—a critical challenge for real-world autonomy. This work has garnered 60 citations, underscoring its significance. Xue has also pioneered semantic probabilistic traversable map generation, enabling robots to navigate complex unstructured terrains like grass and sidewalks, and has advanced SLAM-based topological mapping to create reliable global planners from sparse visual data. His innovative integration of SLAM with deep reinforcement learning for local planning represents a notable achievement, bridging global and local navigation strategies. Additionally, Xue designed a reconfigurable multi-sensor testbed, providing a versatile platform for autonomous systems research. With over 120 total citations across his key works, Xue’s research continues to shape robust, adaptive navigation solutions for robots operating in challenging, dynamic environments.