Bingyu Cai

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About

Bingyu Cai is a researcher advancing intelligent systems for retail and urban environments, with a focus on computer vision and multi-sensor fusion. Their key research areas include deep learning-based object detection and autonomous robot localization, particularly applied to shopping robots and smart city technologies. Cai’s most notable contribution is the development of LSR-YOLO, a lightweight and fast object detection model tailored for retail product identification, which has garnered 6 citations since its 2025 publication. This work addresses the high computational demands of traditional models, enabling efficient deployment in real-time retail settings. Additionally, Cai designed an improved ORB-SLAM3 positioning system that fuses LiDAR and RGB-D sensors, solving critical issues like arbitrary-start localization and map mismatches for indoor shopping robots, earning 2 citations. This multi-sensor fusion approach enhances navigation accuracy and reliability. Cai’s research bridges the gap between advanced AI techniques and practical applications, making strides toward seamless human-robot interaction in commercial spaces. Their work holds promise for transforming retail automation and smart city infrastructure, with potential for broader impact as these technologies scale.