首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Positioning Navigation and Book Accessing/Returning in an Autonomous Library Robot using Integrated Binocular Vision and QR Code Identification Systems
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Positioning Navigation and Book Accessing/Returning in an Autonomous Library Robot using Integrated Binocular Vision and QR Code Identification Systems

机译:使用集成的双目视觉和QR码识别系统在自主图书馆机器人中进行定位导航和书籍访问/归还

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摘要

With rapid advancements in artificial intelligence and mobile robots, some of the tedious yet simple jobs in modern libraries, like book accessing and returning (BAR) operations that had been fulfilled manually before, could be undertaken by robots. Due to the limited accuracies of the existing positioning and navigation (P&N) technologies and the operational errors accumulated within the robot P&N process, however, most of the current robots are not able to fulfill such high-precision operations. To address these practical issues, we propose, for the first time (to the best of our knowledge), to combine the binocular vision and Quick Response (QR) code identification techniques together to improve the robot P&N accuracies, and then construct an autonomous library robot for high-precision BAR operations. Specifically, the binocular vision system is used for dynamic digital map construction and autonomous P&N, as well as obstacle identification and avoiding functions, while the QR code identification technique is responsible for both robot operational error elimination and robotic arm BAR operation determination. Both simulations and experiments are conducted to verify the effectiveness of the proposed technique combination, as well as the constructed robot. Results show that such a technique combination is effective and robust, and could help to significantly improve the P&N and BAR operation accuracies, while reducing the BAR operation time. The implemented autonomous robot is fully-autonomous and cost-effective, and may find applications far beyond libraries with only sophisticated technologies employed.
机译:随着人工智能和移动机器人的飞速发展,现代图书馆中一些乏味而又简单的工作,例如以前可以手动完成的取书和归还(BAR)操作,可以由机器人来完成。但是,由于现有定位和导航(P&N)技术的准确性有限,并且在机器人P&N过程中累积了操作错误,因此,当前大多数机器人都无法实现这种高精度操作。为了解决这些实际问题,我们(据我们所知)首次建议将双目视觉和快速响应(QR)代码识别技术结合在一起以提高机器人的P&N精度,然后构建一个自主库用于高精度BAR操作的机器人。具体而言,双目视觉系统用于动态数字地图构建和自主P&N,以及障碍物识别和回避功能,而QR码识别技术既负责机器人操作错误的消除,又用于机器人手臂BAR操作的确定。进行了仿真和实验,以验证所提出的技术组合以及所构造的机器人的有效性。结果表明,这种技术组合是有效且可靠的,并且可以帮助显着提高P&N和BAR操作的准确性,同时减少BAR操作时间。已实现的自主机器人是完全自主的且具有成本效益,并且仅使用复杂的技术就可以找到远远超出库的应用程序。

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