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，技术和架构可以帮助开发人员构建强大而可靠的无人机，并配备有效的障碍物检测和危险规避方法。NOVAerial Robotics是一家无人机制造商，其中备受欢迎的是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 ** 在不同环境条件下检测物体。因此，在本项目中，我们的目标是研究 ** 并提出解决方案，以解决配备第一人称视角 **（FPV）的单旋翼无人机中的目标检测和危险规避问题。无人机需要在各种动态情况下提供可靠的服务并进行适当的适应。系统 ** 需要跟踪所有情况，以便正常运行。系统有必要通过监测其环境来充分了解其不同的条件和属性。在 ** 成像技术和通信的最新进展已经引入了一个令人难以置信的增长，不同的相机和 ** 各种视觉设备作为一个强大的监控工具。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 ** 并识别它们的交互，包括时间属性。该项目旨在分析从操作中的无人机收集的视频流，用于障碍物检测和危险规避。