Deploying drones for autonomous detection of pavement distress
Name
964698554-MIT.pdf
Description
Full printable version
Size
5.64 MB
Format
Adobe PDF
Checksum (MD5)
571e0bfb3a3e62346dc50da2f6466f4f
Author(s)
Petkova, Mia
Advisor(s)
César A. Hidalgo.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Road repair expenditure comprises a significant portion of US federal and municipal budgets. Inspection and timely maintenance are crucial preventative measures against pavement distress formation that can lower the monetary burden of repairs. Yet state of the art road inspection techniques still employ technicians to perform distress measurements manually. These methods are often too costly, time-consuming, labor-intensive and require technical expertise. Meanwhile, autonomous systems are increasingly deployed in place of human operators where tasks are monotonous and where risk of exposure to hostile conditions is great. As a time-consuming but highly repetitive task, road inspection presents a promising candidate for task automation. Automating road inspection can present significant efficiency gains that can aid agencies in responding to early signs of erosion in a timely manner. In this work, I explore the capacity of drones to perform autonomous pavement inspections. I develop a system that dispatches drones to survey an area, diagnose the presence of pavement distress in real time, and record imagery and coordinates of locations requiring repair. This system presents an alternative to on-ground inspections and tools that draw on crowd-sourced mechanisms to identify potholes. It builds on other recent technological solutions that employ remote sensing to collect and interpret data on pavement health. The results from this mission will be visualized through a web platform that can not only aid cities in consolidating a fragmented and costly data collection process, but also in minimize human error in the identification and prioritization of problem areas.
Description
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 57-61).
Subjects
Program in Media Arts and Sciences ()
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Persistent DSpace Link
