I-Corps: Learning-based Navigation Technology-enabled Service Robots for the Retail Industry

这个I-Corps项目更广泛的影响/商业潜力是开发一种零售服务机器人，该机器人利用为密集拥挤环境开发的最先进的人性化导航技术。根据目前的行业估计，由于库存异常，全球零售商损失了1万亿美元。由于库存管理不善，零售客户经常对缺货项目感到失望，导致客户忠诚度下降。为了在大多数商品都可以在线购买的当前市场趋势中生存下来，实体店需要进行现代化改造，并尽可能使用自动化解决方案，以腾出员工的时间，更加专注于客户体验。这个I-Corps项目的基础是开发一种具有最先进的防撞技术的机器人。它能够在密度大于1人/平方米的人群中运行。该机器人使用商品视觉传感器检测行人移动，并智能地规划一条对人类最不显眼的路径。碰撞避免技术还显著减少了（50%）机器人突然冻结或停止的发生，这是密集场景中的常见现象。I-Corps计划将有助于更好地了解这种机器人在零售业中的应用。该机器人将在拥挤的商店中导航，并进行体积扫描，以捕获有关货架上物品和客户购买模式的实时数据，从而提高商店库存管理的效率和准确性。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of a retail service robot utilizing state-of-the-art, human-friendly navigation technology developed for densely crowded environments. As per the current industry estimates, retailers are losing $1 trillion worldwide due to inventory aberrations. Retail customers are frequently disappointed by out-of-stock items because of poor inventory management, leading to reduced customer loyalty. To survive current market trends in which most items may be purchased online, brick-and-mortar stores need to modernize, and use automated solutions wherever possible to free up associates’ time and focus more on the customer experience. This I-Corps project is based on the development of a robot enabled with state-of-the-art collision avoidance technology. It is capable of operating in crowds of a density greater than 1 person/square meter. The robot detects pedestrian movements using commodity visual sensors and smartly plans a path that is least obtrusive to humans. The collision avoidance technology also significantly reduces (by 50%) the occurrence of the robot suddenly freezing or halting, which is a common phenomenon in dense scenarios. The I-Corps program will help better understand the applications of such a robot in the retail industry. The proposed robot will navigate in a densely crowded store and will perform volumetric scans to capture real-time data about the items on the shelves and customer buying patterns, leading to an increase in efficiency and accuracy in managing a store’s inventory.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.