2026-09-19T18:55:09Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/1571882024-10-10T03:03:23Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Adib, Fadel Herrera, Joshua I. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2024-10-09T18:27:08Z 2024-10-09T18:27:08Z 2024-09 2024-10-07T14:34:30.537Z https://hdl.handle.net/1721.1/157188 We present the design, implementation and evaluation of MilliNavigator, an autonomous navigation system for drones capable of mapping, path-planning, self-localizing, and navigating in indoor environments by leveraging strategically-placed millimeter wave anchors. Autonomous drones are an increasingly relevant tool for completing and automating hard-to-reach tasks. State of the art navigation systems rely primarily on cameras and GPS for environmental perception and self-localization. These solutions can impose restrictions on existing systems, which limit their navigable environment to well-lit, outdoors, and unobstructed paths. This thesis presents MilliNavigator, the first system to use millimeter wave radar and anchor-aware path planning to achieve high accuracy, 6DOF, online localization. By generating a localization precision score map from known anchor deployments, the system jointly optimizes travel distance and localization performance. We implemented and evaluated MilliNavigator on a drone built with commercial, off-the-shelf parts. We ran over 165 successful missions across 7 different tag deployments. Our system successfully achieved 7.9cm overall median error and had a 90th percentile error of less than 21cm. M.Eng. Massachusetts Institute of Technology Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/ Autonomous UAV Navigation using Millimeter Wave Radar Thesis application/pdf Master Master of Engineering in Electrical Engineering and Computer Science Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e86416e2-59f8-470f-90e8-5c09270912a1"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Autonomous UAV Navigation using Millimeter Wave Radar</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2024-09</PublicationDate> <Authors> <Author> <DisplayName>Herrera, Joshua I.</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License> <Abstract>We present the design, implementation and evaluation of MilliNavigator, an autonomous navigation system for drones capable of mapping, path-planning, self-localizing, and navigating in indoor environments by leveraging strategically-placed millimeter wave anchors. Autonomous drones are an increasingly relevant tool for completing and automating hard-to-reach tasks. State of the art navigation systems rely primarily on cameras and GPS for environmental perception and self-localization. These solutions can impose restrictions on existing systems, which limit their navigable environment to well-lit, outdoors, and unobstructed paths. This thesis presents MilliNavigator, the first system to use millimeter wave radar and anchor-aware path planning to achieve high accuracy, 6DOF, online localization. By generating a localization precision score map from known anchor deployments, the system jointly optimizes travel distance and localization performance. We implemented and evaluated MilliNavigator on a drone built with commercial, off-the-shelf parts. We ran over 165 successful missions across 7 different tag deployments. Our system successfully achieved 7.9cm overall median error and had a 90th percentile error of less than 21cm.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>