dc.contributor.authorBharath Kalyanen_US
dc.identifier.citationBharath, K. (2011). Unified random finite set theoretic approach to autonomous underwater vehicle navigation. Doctoral thesis, Nanyang Technological University, Singapore.
dc.description216 p.en_US
dc.description.abstractThis thesis addresses the problem of navigation, localization and mapbuilding in an unknown and unstructured environment and its application to an autonomous underwater vehicle (AUV). Given the dynamic nature of the underwater environment and the limitations of traditional baseline based systems, the inability to use GPS underwater, and the range limited optical vision systems, our approach for overcoming these navigation limitations has been to embrace a feature based simultaneous localization and mapping (SLAM) framework while explicitly exploiting the available navigational sensor suite and rich blazed array sonar imagery that is commonly used in underwater explorations. The most common formulation of the feature based SLAM problem is founded on a vector based stochastic framework, where the sensor models and the vehicle models are represented in state space form and the joint posterior or its statistics are obtained based on recursive Bayesian estimation.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleUnified random finite set theoretic approach to autonomous underwater vehicle navigationen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.supervisorArjuna Balasuriya
dc.contributor.supervisorWijerupage Sardha Wijesomaen_US
dc.description.degreeDOCTOR OF PHILOSOPHY (EEE)en_US

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