An onboard simultaneous localization and mapping system for unmanned aerial vehicles

无人机机载同步定位与测绘系统

• 批准号: 485611-2015
• 负责人: Derpanis, Konstantinos
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=585086
• 关键词: onboard; simultaneous; localization; mapping; system

The goal of this project is to develop a Simultaneous Localization and Mapping (SLAM) system for use on multi-rotor Unmanned Aerial Vehicles (UAVs) flying in indoor environments. This system will rely solely on onboard sensing and computing with no GPS. It will provide pilots with increased situational awareness by creating a constantly updating map of the environment being explored. UAVs are emerging as a viable, low-cost platform for indoor applications. There is a growing list of commercial applications, including surveillance, exploration (e.g., mining operations and disaster sites), agriculture, and filmmaking. While there has been significant work done in this area, existing systems have several limitations that make them unsuitable for many commercial applications. For instance, data is often processed offline. This manner of data processing is not ideal because it precludes feedback to the pilot during flight, and more generally prohibits real-time applications. While real-time data processing approaches exist, they do so by streaming data back to a powerful base station computer. In real-world applications, communication may often be hampered due to wireless signal interference. In this project, we will investigate an approach whereby the UAV operates in a semi-autonomous mode. In this mode, the UAV maintains an onboard map allowing it to avoid obstacles and localize itself within the environment. The pilot is tasked with providing the UAV macro commands. For example, the pilot may identify the UAV's desired destination, while the UAV computes the safest navigation route and proceeds along it. This approach not only increases situational awareness for the pilot as the onboard map is streamed back to the user interface but also is robust to wireless signal interference, as the communication between controller and UAV does not have to be in real-time. We will examine the viability of such a system as a commercial product. This entails optimizing between the speed of the map generation system, the map resolution and accuracy, and the monetary cost of the hardware.

该项目的目标是开发一个同时定位和地图（SLAM）系统，用于 在室内环境中飞行的多旋翼无人机（UAV）。该系统将完全依赖于 没有GPS的机载传感和计算。它将通过以下方式为飞行员提供更强的态势感知能力： 创造一个不断更新的环境地图被探索。 无人机正在成为室内应用的可行、低成本平台。有越来越多的 商业应用，包括监视，勘探（例如，采矿作业和灾害现场）， 农业和电影制作。虽然在这方面已经做了大量工作，但现有系统 这使得它们不适合于许多商业应用。例如，数据通常 离线处理。这种数据处理方式并不理想，因为它排除了在飞行期间对飞行员的反馈。 飞行，更普遍地禁止实时应用。虽然存在实时数据处理方法， 它们通过将数据流传输回功能强大的基站计算机来实现这一点。在实际应用中， 由于无线信号干扰，通信经常会受到阻碍。 在这个项目中，我们将研究一种方法，使无人机在半自主模式下运行。在 在这种模式下，无人机保持机载地图，使其能够避开障碍物，并将自身定位在 环境飞行员的任务是提供无人机的宏命令。例如，飞行员可以 确定无人机的期望目的地，同时无人机计算最安全的导航路线并继续前进 沿着它。这种方法不仅增加了飞行员的态势感知，因为机载地图是流式传输的 而且对于无线信号干扰是鲁棒的，因为 控制器和无人机不必实时。我们会研究这个制度的可行性， 商业产品。这需要优化地图生成系统、地图的速度 分辨率和准确性，以及硬件的货币成本。