Huaiyu Xiao
Papers
2
Total Citations
4
H-Index
2
About
Huaiyu Xiao is a robotics researcher whose work focuses on advancing robot autonomy in open, dynamic environments. His key research areas include task planning under uncertainty, hybrid reasoning systems, and the integration of sensing and acting for robust robot operation. Xiao's major contributions center on developing novel planning frameworks that address the critical challenge of information incompleteness during plan execution. In his influential papers, "Towards Adjoint Sensing and Acting Schemes and Interleaving Task Planning for Robust Robot Plan" (2021) and "Towards a Hybrid-ASP Planning Approach With Adjoint Observation for Incomplete Task-Relevant Information" (2021), he proposes innovative approaches that combine Answer Set Programming (ASP) with adjoint observation mechanisms. These frameworks enable robots to dynamically sense their environment and interleave planning with execution, significantly improving task robustness when faced with partial observability and unexpected state changes. While his citation counts (2 each) reflect the early stage of his career, the conceptual depth of his work—particularly the hybrid-ASP approach—positions him as an emerging voice in task planning for autonomous systems. His research is particularly valuable for students and researchers working on real-world robot deployment where environmental uncertainty is a fundamental constraint.
Research Focus
Key Achievements
Top Papers
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- 2