YorkSpace has migrated to a new version of its software. Access our Help Resources to learn how to use the refreshed site. Contact diginit@yorku.ca if you have any questions about the migration.
 

Planetary Micro-Rovers with Bayesian Autonomy

Simple item page
dc.contributor.advisorQuine, Brendan
dc.creatorPost, Mark Andrew
dc.date.accessioned2014-07-16T03:22:30Z
dc.date.available2014-07-16T03:22:30Z
dc.date.copyright2014-04-01
dc.date.issued2014-07-09
dc.date.updated2014-07-09T16:54:58Z
dc.degree.disciplineEarth & Space Science
dc.degree.levelDoctoral
dc.degree.namePhD - Doctor of Philosophy
dc.description.abstractIn this dissertation, we present the Beaver μrover, a 6kg solar-powered planetary rover that is designed to perform exploration missions such as the Northern Light Mars mission, as well as to extend the capabilities of modern robotics here on Earth. By developing systems from the ground up using a pragmatic design approach for modularity and expandability, commercial hardware, open-source software, and novel implementations of probabilistic algorithms, we have obtained a comprehensive set of hardware and software designs that can form the basis for many kinds of intelligent but low-cost robots. A lightweight tubular chassis that can be simply deployed protects sensors, actuators, and wiring, and a novel four-wheel independently driven and passively actuated suspension with enclosed brushless gear motors can stably handle steep slopes and low obstacles. A nanosatellite-sized electronics stack incorporates Linux or dedicated RTOS computing on the ARM architecture, highly-efficient battery charging and power conversion, MEMS and external sun sensors, a powerful hybrid motor controller, and a vision system. Separate rovers and programmable components communicate using a novel network communications architecture over synchronous serial buses and mesh network radio communications. Intelligent autonomy is made possible using probabilistic methods programmed with fixed-point arithmetic for efficiency, incorporating Kalman filters and a Bayesian network constructed both from prior knowledge and from the implicit structure of the hardware and software present and used for inference and decision-making. Navigation makes use of both external sensors and visual SLAM by using optical flow and structure-from-motion methods. Detailed descriptions and comparisons of all systems are given, and it is shown that using a basic set of sensors and the vision system, basic navigational and problem-solving tasks can be performed. Thermal vacuum testing of components is also done to validate their operation under space conditions.en_US
dc.identifier.urihttp://hdl.handle.net/10315/27661
dc.language.isoenen_US
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectRoboticsen_US
dc.subjectElectrical engineeringen_US
dc.subjectMechanical engineeringen_US
dc.subject.keywordsLinuxen_US
dc.subject.keywordsRoboticsen_US
dc.subject.keywordsRoversen_US
dc.subject.keywordsPlanetary robotsen_US
dc.subject.keywordsPlanetary explorationen_US
dc.subject.keywordsMarsen_US
dc.subject.keywordsNorthern Lighten_US
dc.subject.keywordsOff-the-shelf hardwareen_US
dc.subject.keywordsSpace hardwareen_US
dc.subject.keywordsRover mechanicsen_US
dc.subject.keywordsSuspension designen_US
dc.subject.keywordsChassis controlen_US
dc.subject.keywordsNano-satellitesen_US
dc.subject.keywordsOn-board computersen_US
dc.subject.keywordsEmbedded systemsen_US
dc.subject.keywordsPower electronicsen_US
dc.subject.keywordsMotor drivesen_US
dc.subject.keywordsDC motor controlen_US
dc.subject.keywordsInertial sensingen_US
dc.subject.keywordsSun sensingen_US
dc.subject.keywordsMachine visionen_US
dc.subject.keywordsRobot communicationsen_US
dc.subject.keywordsMesh networkingen_US
dc.subject.keywordsFixed-point algorithmsen_US
dc.subject.keywordsBayesian networksen_US
dc.subject.keywordsBayesian programmingen_US
dc.subject.keywordsProbabilistic roboticsen_US
dc.subject.keywordsProbabilistic mappingen_US
dc.subject.keywordsKalman filtersen_US
dc.subject.keywordsNonlinear controlen_US
dc.subject.keywordsMachine visionen_US
dc.subject.keywordsOptical flowen_US
dc.subject.keywordsStructure-from-motionen_US
dc.subject.keywordsSLAMen_US
dc.subject.keywordsThermal vacuum testingen_US
dc.subject.keywordsReal-time operating systemsen_US
dc.titlePlanetary Micro-Rovers with Bayesian Autonomyen_US
dc.typeElectronic Thesis or Dissertation

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Post_Mark_A_2014_PhD.pdf
Size:
28.87 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
license.txt
Size:
1.83 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
No Thumbnail Available
Name:
YorkU_ETDlicense.txt
Size:
3.38 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Earth & Space Science

All items in the YorkSpace institutional repository are protected by copyright, with all rights reserved except where explicitly noted.