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Development of a Quadrotor-type UAV Platform for Autonomous Collision Avoidance under Teleoperation

Title
Development of a Quadrotor-type UAV Platform for Autonomous Collision Avoidance under Teleoperation
Translated Title
원격조종 기반 쿼드로터 타입 무인항공기의 자율충돌회피 시스템 구축
Authors
SangYong Park
DGIST Authors
Park, SangYong; Kung, JaehaKim, Kyoung-Dae
Advisor(s)
김경대
Co-Advisor(s)
Jaeha Kung
Issue Date
2020
Available Date
2020-06-23
Degree Date
2020-02
Type
Thesis
Description
UAV, Autonomous collision avoidance, VPF, Sensor fusion
Abstract
In recent years, unmanned aerial vehicle (UAV) systems have been used successfully in many tasks such as search and rescue, remote sensing, mapping, exploration, surveillance, and many other civil and military applications. In general, an unmanned aerial vehicle is a powered aircraft that can be operated remotely or automatically without human boarding. Therefore, it has an advantage over general aircraft in terms of size and weight, so it can be usefully used for various tasks as described above. Accordingly, the development of unmanned aerial vehicle technology and the growing demand for unmanned aerial vehicles are expected, and various types of high performance unmanned aerial vehicles have been developed and launched. As the use of unmanned aerial vehicles has soared, there has been a growing interest in unmanned aerial vehicle collision avoidance technology as concerns about collisions with buildings, aerial installations, and even collisions with airplane. However, as one may know, it is actually not a trivial task to remote control a UAV safely, especially in a cluttered environment. Hence, autonomous collision avoidance is considered as one of the essential capabilities that UAVs must provide. And also, the autonomy level of robotic system is still restricted by the deficiency of a robust and reliable perception, and of a higher cognitive ability that allows sophisticated decision making in real world environment. This is especially true for robots that have high degrees of freedom such as UAV. Thus, in many cases, human supervisory is still required to perform high level decision making while UAVs execute their local autonomy such as obstacle avoidance. Therefore, to ensure that the UAV safely follows the human operator's command, the high level of decision-making that can be performed by the human operator and the proper integration of local autonomy that the UAV can perform on its own are essential. The representative local autonomy that UAV can perform is the autonomous collision avoidance of the UAV itself. Therefore, there is no doubt that autonomous collision avoidance is indeed one of the essential capabilities that a UAV should have for the sake of UAV operational safety. Therefore, in this Theses, present a highly reliable autonomous collision avoidance algorithm, Vehicle-Centered Potential Function (VPF), and verify the performance through extensive simulation using the robot simulation software V-REP. After successfully verifying the VPF-based autonomous collision avoidance algorithm through simulation, need to verify the performance on a real UAV platform. Therefore, as part of an extensive research project on autonomous collision avoidance of remotely operated UAVs, this particular study focuses on the development of a real UAV platform and uses it to evaluate collision avoidance performance through experiments. More specifically, designed both UAV's hardware and software systems, including ground control systems. In addition, sensors are mounted on UAV for object detection and identification and a high confidence recognition system is established through sensor fusion. Through the above researches, built an autonomous collision avoidance system of UAV and verify the performance through experiments.
Table Of Contents
Ⅰ. Introduction 1 Ⅱ. Related Work 2 Ⅲ. Configuration of a UAV platform 5 3.1 Hardware System 6 3.2 Software System 7 3.3 Custom Software System for Collision Avoidance 10 Ⅳ. Object Detection and Tracking 11 4.1 Sensor Fusion 12 4.2 Moving object Detection and tracking 15 4.3 Local Map for Static Object Detection 23 Ⅴ. Collision Avoidance 27 Ⅵ. Conclusions 34
URI
http://dgist.dcollection.net/common/orgView/200000285237
http://hdl.handle.net/20.500.11750/12014
DOI
10.22677/Theses.200000285237
Degree
Master
Department
Information and Communication Engineering
University
DGIST
Related Researcher
Files:
Collection:
Department of Information and Communication EngineeringThesesMaster


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