Terrain Classification and Navigability Analysis in Unstructured Outdoor Environments

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dc.contributor.advisorLin, Ming Cen_US
dc.contributor.authorGuan, Tianruien_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2022-02-03T06:31:48Z
dc.date.available2022-02-03T06:31:48Z
dc.date.issued2021en_US
dc.description.abstractWe present a new learning-based method for identifying safe and navigable regions inoff-road terrains and unstructured environments from RGB images. Our approach consists of classifying groups of terrains based on their navigability levels using coarse-grained semantic segmentation. We propose a transformer-based deep neural network architecture that uses a novel group-wise attention mechanism to distinguish between navigability levels of different terrains. Our group-wise attention heads enable the network to explicitly focus on the different groups and improve the accuracy. We show through extensive evaluations on the RUGD and RELLIS-3D datasets that our learning algorithm improves visual perception accuracy in off-road terrains for navigation. We compare our approach with prior work on these datasets and achieve an improvement over the state-of-the-art mIoU by 6.74-39.1% on RUGD and 3.82-10.64% on RELLIS-3D. In addition, we deploy our method on a Clearpath Jackal robot. Our approach improves the performance of the navigation algorithm in terms of average progress towards the goal by 54.73% and the false positives in terms of forbidden region by 29.96%.en_US
dc.identifierhttps://doi.org/10.13016/sd2e-izm5
dc.identifier.urihttp://hdl.handle.net/1903/28387
dc.language.isoenen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pquncontrolledAttentionen_US
dc.subject.pquncontrolledOutdoor Navigationen_US
dc.subject.pquncontrolledTerrain Segmentationen_US
dc.subject.pquncontrolledTraversabilityen_US
dc.subject.pquncontrolledUnstructured Environmenten_US
dc.titleTerrain Classification and Navigability Analysis in Unstructured Outdoor Environmentsen_US
dc.typeThesisen_US

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