PFI:AIR - TT: AGV-3D: A Low-Cost, Infrastructure-free Localization Solution for FlexibleWarehouse Automation

这个PFI: AIR技术翻译项目专注于翻译技术，以满足对基础设施自由定位系统的需求，以准确估计大型仓库环境中自动引导车辆（AGV）的位置和方向。该系统被称为AGV- 3d，它非常重要，因为它增强了当前的AGV技术，从而通过提供可靠和安全的方式来满足材料移动需求，从而提高了美国制造业的效率。该项目将使AGV- 3d原型机集成到实际的AGV系统中，并在具有代表性的仓库环境中进行演示。AGV-3D具有以下独特功能：它集成了最新的3D成像技术，可以在大型仓库设施中实现AGV车辆的稳健和准确定位，而无需在环境中集成电线，磁铁或反射器。这些特点提供了以下优势：与市场上领先的2D激光制导技术相比，每辆车的成本更低，设施安装成本更低，设施灵活性更高。该项目解决了以下技术差距，因为它从研究发现转化为商业应用。第一个重大挑战是agv所需的定位精度在1厘米左右。其次，定位系统必须非常健壮，因为AGV仓库安装需要非常高的可用性。不幸的是，与当前的二维激光制导技术不同，正确地关联地标特征要困难得多，因为人工后向反射器目标不会安装在环境中。因此，在数据关联和重建方面都存在重大挑战。为了应对这些挑战，AGV-3D利用3D数据进行环境映射和地标特征分割。首先，对设施进行三维重建，提取突出的自然特征作为地标。接下来，基于地图的定位方法利用3D激光雷达实现3D特征到地标的匹配，从而最大限度地减少数据关联错误的可能性。通过采用最新的3D传感器系统，AGV车辆将能够实时跟踪这些3D特征。结合基于地图的定位方法，期望达到厘米级的精度。此外，参与该项目的研究生将通过系统开发，以及与机器人、AGV和3D传感领域的公司直接互动，获得创新和技术转化经验。

This PFI: AIR Technology Translation project focuses on translating technology to fill the need for an infrastructure free localization system to accurately estimate the position and orientation of an automated guided vehicle (AGV) in large-scale warehouse environments. The system is called AGV-3D, and it is important because it enhances current AGV technology, which in turn improves the efficiency of U.S. manufacturing by providing a reliable and safe means of meeting material movement demands. The project will result in an AGV-3D prototype being integrated into an actual AGV system, and demonstrated in a representative warehouse environment. AGV-3D has the following unique features: it integrates the latest in 3D imaging technologies to enable robust and accurate localization of an AGV vehicle in a large-scale warehouse facility without the integration of wires, magnets, or reflectors in the environment. These features provide the following advantages: lower per-vehicle cost, lower facility installation cost, and increased facility flexibility when compared to the leading competing 2D laser guidance technology in this market space. This project addresses the following technology gap(s) as it translates from research discovery toward commercial application. The first significant challenge is that the required positioning accuracy of AGVs is on the order of 1 cm. The second is that the localization system must be extremely robust as AGV warehouse installations require very high levels of availability. Unfortunately, correctly associating landmark features will be far more difficult as unlike current 2D laser guidance technologies, artificial retroreflector targets will not be installed in the environment. Thus, there are significant challenges in both data association and reconstruction. To meet these challenges, AGV-3D leverages 3D data for both mapping the environment and landmark feature segmentation. First, a 3D reconstruction of the facility is created to extract salient natural features as landmarks. Next, a map-based localization approach leverages 3D LIDAR to enable 3D feature-to-landmark matching which minimizes the potential for data association errors. By employing the latest in 3D sensor systems, AGV vehicles will be able to track these 3D features in real-time. In conjunction with the map-based localization approach, centimeter level accuracy is expected. In addition, graduate students involved in this project will receive innovation and technology translation experiences through system development, and through direct interactions with companies in the robotics, AGV, and 3D sensing spaces.