Object detection and hazard avoidance with FPV equipped single-rotor UAVs

使用配备 FPV 的单旋翼无人机进行物体检测和危险规避

• 批准号: 530001-2018
• 负责人: Azim, Akramul
• 金额: $ 1.82万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644382
• 关键词: Object; detection; hazard; avoidance; FPV

Design challenges exist for obstacle detection and hazard avoidance of unmanned aerial vehicle (UAV)**systems. Our research addresses this challenge by analyzing tools, techniques and architectures that assist**developers in building robust and reliable UAVs equipped with efficient obstacle detection and hazard**avoidance methods. NOVAerial Robotics is a manufacturer of UAV and a well-received one is Procyon 800E**which a single rotor helicopter style UAV. One of the challenges in operating UAVs by NOVAerial robotics is**the detection of objects in different environmental conditions. Therefore, in this project we aim to investigate**and propose solutions to address the problem of object detection and hazard avoidance in first person view**(FPV) equipped single rotor UAVs.**UAVs need to provide reliable service with appropriate adaptation in various dynamic situations. The system**needs to keep track of all the situations for proper functioning. It is necessary for the system to have sufficient**knowledge of its different conditions and properties by monitoring its environment. Recent advances in**imaging techniques and communications have introduced an incredible growth of different cameras and**various visual devices as a powerful monitoring tool. Moreover, video provides detailed information on the**interactions as opposed to tracing or data logging. Through analyzing video data, we can detect different events**and identify their interactions including timing properties. This project aims to analyze video streams gathered**from operating UAVs for obstacle detection and hazard avoidance.

无人机 (UAV)** 系统的障碍物检测和危险规避存在设计挑战。我们的研究通过分析工具、技术和架构来解决这一挑战，这些工具、技术和架构可帮助**开发人员构建强大而可靠的无人机，并配备高效的障碍物检测和危险**避免方法。 NOVAerial Robotics 是一家无人机制造商，其中一款广受好评的产品是 Procyon 800E**，这是一款单旋翼直升机式无人机。 NOVAerial 机器人操作无人机的挑战之一是**不同环境条件下的物体检测。因此，在这个项目中，我们的目标是研究**并提出解决方案，以解决第一人称视角**（FPV）配备的单旋翼无人机的目标检测和危险避免问题。**无人机需要提供可靠的服务，并进行适当的适应各种动态情况。系统**需要跟踪所有情况才能正常运行。系统有必要通过监视其环境来充分了解其不同的条件和属性。 **成像技术和通信的最新进展带来了不同摄像机和**各种视觉设备的惊人增长，作为强大的监控工具。此外，视频提供了有关交互的详细信息，而不是跟踪或数据记录。通过分析视频数据，我们可以检测不同的事件**并识别它们的相互作用，包括时序属性。该项目旨在分析从操作无人机收集的视频流，以进行障碍物检测和危险避免。