A variational approach to mapping: an exploration of map representation for SLAM

dc.contributor.advisorHogue, Andrew
dc.contributor.authorKhattak, Saad Rustam
dc.date.accessioned2012-10-11T14:10:53Z
dc.date.accessioned2022-03-29T17:30:07Z
dc.date.available2012-10-11T14:10:53Z
dc.date.available2022-03-29T17:30:07Z
dc.date.issued2012-07-01
dc.degree.disciplineComputer Science
dc.degree.levelMaster of Science (MSc)
dc.description.abstractSimultaneous Localization and Mapping (SLAM) algorithms are used by autonomous robots to build or update maps of an environment while maintaining their position simultaneously. A fundamental open problem in SLAM is the e ective representation of the map in unknown, ambiguous, complex, dynamic environments. Representing such environments in a suitable manner is a complex task. Existing approaches to SLAM use map representations that store individual features (range measurements, image patches, or higher level semantic features) and their locations in the environment. The choice of how the map is represented produces limitations which in many ways are unfavourable for application in real-world scenarios. In this thesis, a new approach to SLAM is explored that rede nes sensing and robot motion as acts of deformation of a di erentiable surface. Distance elds and level set methods are utilized to de ne a parallel to the components of the SLAM estimation process and an algorithm is developed and demonstrated. The variational framework developed is capable of representing complex dynamic scenes and spatially varying uncertainty for sensor and robot models.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.identifier.urihttps://hdl.handle.net/10155/273
dc.language.isoenen
dc.subjectSLAMen
dc.subjectLevel seten
dc.subjectDistance fieldsen
dc.subjectImplicit surfacesen
dc.subjectMappingen
dc.titleA variational approach to mapping: an exploration of map representation for SLAMen
dc.typeThesisen
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Ontario Institute of Technology
thesis.degree.nameMaster of Science (MSc)

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