Xuebing Yue

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About

Xuebing Yue is a robotics researcher focused on advancing human-robot interaction and autonomous navigation. His key research areas include multi-modal robotic systems, semantic mapping, and intelligent path planning. Yue's work on the Pepper robot platform demonstrates a practical approach to enhancing service robot flexibility, integrating RGB-D cameras, voice systems, and control architectures to move beyond preset programs. His 2024 paper on target grasping and multi-modal interaction with Pepper robot (1 citation) addresses critical limitations in commercial service robots used in homes, shopping malls, and hotels. In his 2025 work on adaptive-optimized semantic point cloud mapping with YOLO11-seg (1 citation), Yue tackles a fundamental challenge in robotics: moving beyond traditional geometric SLAM to enable robots to interpret and interact with their environment at a semantic level. This integrated framework for semantic map construction and navigation validation represents an important step toward more intelligent, context-aware robotic systems. Though early in his career, Yue's research bridges the gap between perception and action, contributing to the development of robots that can understand and navigate complex human environments more effectively.