Attention and Sensor Planning in Autonomous Robotic Visual Search

Simple item page
dc.contributor.advisorTsotsos, John K.
dc.creatorRasouli, Amir
dc.date.accessioned2015-08-28T15:23:29Z
dc.date.available2015-08-28T15:23:29Z
dc.date.copyright2015-01-19
dc.date.issued2015-08-28
dc.date.updated2015-08-28T15:23:29Z
dc.degree.disciplineComputer Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractThis thesis is concerned with the incorporation of saliency in visual search and the development of sensor planning strategies for visual search. The saliency model is a mixture of two schemes that extracts visual clues regarding the structure of the environment and object specific features. The sensor planning methods, namely Greedy Search with Constraint (GSC), Extended Greedy Search (EGS) and Dynamic Look Ahead Search (DLAS) are approximations to the optimal solution for the problem of object search, as extensions to the work of Yiming Ye. Experiments were conducted to evaluate the proposed methods. They show that by using saliency in search a performance improvement up to 75% is attainable in terms of number of actions taken to complete the search. As for the planning strategies, the GSC algorithm achieved the highest detection rate and the best efficiency in terms of cost it incurs to explore every percentage of an environment.
dc.identifier.urihttp://hdl.handle.net/10315/30014
dc.language.isoen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectRobotics
dc.subjectArtificial intelligence
dc.subjectComputer engineering
dc.subject.keywordsRobotic
dc.subject.keywordsAutonomy
dc.subject.keywordsVisual search
dc.subject.keywordsVisual attention
dc.subject.keywordsMotion planning
dc.subject.keywordsSaliency
dc.subject.keywordsSensor planning
dc.subject.keywordsArtificial intelligence
dc.subject.keywords3D search
dc.subject.keywordsObject search
dc.subject.keywordsObject detection
dc.titleAttention and Sensor Planning in Autonomous Robotic Visual Search
dc.typeElectronic Thesis or Dissertationen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Rasouli_Amir_2015_Masters.pdf
Size:
4.93 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:
Plain Text
Description:
Download
No Thumbnail Available
Name:
YorkU_ETDlicense.txt
Size:
3.38 KB
Format:
Plain Text
Description:
Download

Collections

Computer Engineering

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