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

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
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
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,视频提供了关于 ** 互动的详细信息,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。
英文摘要
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.
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