Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/2171
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dc.contributor.authorRao, Navvrat-
dc.contributor.authorAnand, Saket (Advisor)-
dc.date.accessioned2026-09-18T11:30:47Z-
dc.date.available2026-09-18T11:30:47Z-
dc.date.issued2024-04-26-
dc.identifier.urihttp://repository.iiitd.edu.in/xmlui/handle/123456789/2171-
dc.description.abstractThis thesis project, titled Multi-Modal Sensor Fusion for Geometric and Semantic Scene Understanding with Graphs, aims to highlight the constraints inherent in sensors such as LiDAR and cameras and highlight current tools and algorithms for clear interpretation of the environment to occupancy grid. We propose a solution using late fusion for these sen sors, then apply the Kalman filter to the fused data to estimate the detected obstacle’s state. The information derived from this process will then be integrated into the occupancy grid for enhanced accuracy and navigational utility.en_US
dc.language.isoen_USen_US
dc.publisherIIIT-Delhien_US
dc.subjectAutonomous Drivingen_US
dc.subjectDeep Fusionen_US
dc.subjectEarly Fusionen_US
dc.subjectMulti-Modal Sensor Fusionen_US
dc.subjectOccupancy Griden_US
dc.titleMulti-modal sensor fusion for geometric and semantic scene understanding with graphsen_US
dc.typeOtheren_US
Appears in Collections:Year-2024

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