A Low-cost Simultaneous Localization And Mapping Algorithm For Last-mile Indoor Delivery

Wenming Wang, Wei Zhao, Xiaohan Wang, Zhihong Jin, Yuanchen Li, Troy Runge
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引用次数: 9

Abstract

With the development of e-commerce, more and more express packages need to be delivered. The Last-mile indoor task always takes most time of a whole delivery due to the complex and unfamiliar indoor environment. Generally, there aren’t enough existing indoor localization algorithms that are able to meet the business needs. To benefit the public, in this paper, an advanced low-cost and accurate intelligent localization and mapping algorithm is proposed. Three strengths, according to the experiment results, are concluded. First, the algorithm could run on Android devices, and it is able to save the cost of infrastructure as well as battery resources. Second, the algorithm can achieve an accuracy of less than 5cm, which is enough for general commercial purposes. Last, the system could intelligently shift the sensors between the Inertial Measurement Unit (IMU) sensors and the camera. To test our algorithm, we used the robot to execute the delivery of an indoor mailbox, obtaining a result of high accuracy (>95%) and low battery cost (saving more than 56%). Our algorithm is possible to be deployed in autonomous delivery vehicles or drones to provide last-mile delivery service.
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最后一英里室内配送的低成本同步定位与映射算法
随着电子商务的发展,越来越多的快递包裹需要投递。由于室内环境的复杂和不熟悉,最后一英里的室内配送往往占据整个配送过程的大部分时间。一般来说,现有的室内定位算法不足以满足业务需求。为了造福大众,本文提出了一种先进的低成本、精确的智能定位与制图算法。根据实验结果,总结出了三种优势。首先,该算法可以在Android设备上运行,并且能够节省基础设施成本和电池资源。其次,该算法可以达到小于5cm的精度,足以满足一般商业用途。最后,该系统能够在惯性测量单元(IMU)传感器和摄像机之间实现传感器的智能切换。为了测试我们的算法,我们使用机器人执行室内邮箱的投递,获得了高精度(>95%)和低电池成本(节省56%以上)的结果。我们的算法可以部署在自动配送车辆或无人机上,提供最后一英里的配送服务。
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