Grant: Engage Grants Program

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.