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dc.contributor.authorDharmadhikari, Mihir
dc.contributor.authorNguyen, Dinh Huan
dc.contributor.authorMascarich, Frank
dc.contributor.authorKhedekar, Nikhil Vijay
dc.contributor.authorAlexis, Konstantinos
dc.date.accessioned2022-04-04T10:48:04Z
dc.date.available2022-04-04T10:48:04Z
dc.date.created2022-01-18T16:26:00Z
dc.date.issued2021
dc.identifier.isbn1665447044
dc.identifier.urihttps://hdl.handle.net/11250/2989538
dc.description.abstractIn this paper we present the complete system design for an aerial robot capable of autonomous exploration inside natural cave environments. Cave networks involve diverse and complicated topologies, complex geometries and degraded conditions rendering the process of robotic mapping a particularly daunting adventure. In response to these challenges, we outline the core algorithmic modules relating to localization and mapping, exploration path planning and control, alongside the developed perception and computing solutions onboard an aerial robot tailored to undertake such complex tasks given no prior information for the cave environments in which it is deployed. A set of extensive results is presented including both simulation studies in multi-branching and maze-like cave environments, as well as field experiments inside the Moaning Caverns natural cave environment in California, US.en_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartof2021 International Conference on Unmanned Aircraft Systems (ICUAS)
dc.titleAutonomous Cave Exploration using Aerial Robotsen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.identifier.doi10.1109/ICUAS51884.2021.9476870
dc.identifier.cristin1983943
cristin.ispublishedtrue
cristin.fulltextpostprint


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