Xuyang Shao
Papers
10
Total Citations
206
H-Index
8
About
Xuyang Shao is a robotics researcher whose work sits at the intersection of autonomous mobile robotics, semantic understanding, and human-robot interaction, with a particular focus on making service robots more capable and intelligent in real-world home environments. His most influential contribution — "Home Service Robot Task Planning Using Semantic Knowledge and Probabilistic Inference" (2020, 49 citations) — established a foundational framework for reasoning-driven robot autonomy. Building on this, Shao has made significant strides in robotic object search, developing metric-topological mapping strategies and semantic grounding schemes that enable robots to locate objects dynamically in open, ever-changing environments (37 and 27 citations respectively). His research further extends into safe navigation, proposing laser-visual fusion safety strategies and user preference-aware navigation systems that prioritize both physical safety and human comfort. Shao has also tackled the challenging problem of active object detection, introducing behavior cloning and deep Q-learning approaches that improve training efficiency over conventional reinforcement learning methods. More recently, his work on personalized comfort spaces signals a growing commitment to socially aware robotics. Collectively, his portfolio reflects a coherent and ambitious vision for robots that are not only technically capable but genuinely suited to living alongside people.
Research Focus
Key Achievements
Top Papers
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- 2Building Metric-Topological Map to Efficient Object Search for Mobile Robot37 citations · 2021
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- 9A 2D Mapping Method Based on Virtual Laser Scans for Indoor Robots6 citations · 2021
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