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arXiv · 2503.07997

A Survey of Challenges and Sensing Technologies in Autonomous Retail Systems

Shimmy Rukundo·David Wang·Front Wongnonthawitthaya·Youssouf Sidibé·Minsik Kim·Emily Su·Jiale Zhang
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Abstract

Autonomous stores leverage advanced sensing technologies to enable cashier-less shopping, real-time inventory tracking, and seamless customer interactions. However, these systems face significant challenges, including occlusion in vision-based tracking, scalability of sensor deployment, theft prevention, and real-time data processing. To address these issues, researchers have explored multi-modal sensing approaches, integrating computer vision, RFID, weight sensing, vibration-based detection, and LiDAR to enhance accuracy and efficiency. This survey provides a comprehensive review of sensing technologies used in autonomous retail environments, highlighting their strengths, limitations, and integration strategies. We categorize existing solutions across inventory tracking, environmental monitoring, people-tracking, and theft detection, discussing key challenges and emerging trends. Finally, we outline future directions for scalable, cost-efficient, and privacy-conscious autonomous store systems.

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Shimmy Rukundo, David Wang, Front Wongnonthawitthaya, Youssouf Sidibé, Minsik Kim, Emily Su, Jiale Zhang. 2025-03-11. A Survey of Challenges and Sensing Technologies in Autonomous Retail Systems. https://arxiv.org/abs/2503.07997

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