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dc.contributor.authorYu, Qingen_US
dc.contributor.authorZhang, Mingchengen_US
dc.contributor.authorLow, Kin Huaten_US
dc.identifier.citationYu, Q., Zhang, M. & Low, K. H. (2022). Preliminary study on drone navigation in urban environments using visual odometry and partially observable Monte Carlo planning. AIAA AVIATION 2022 Forum, 2022-3765-.
dc.description.abstractDue to the recent technological development in drone technology, a drone is used in many applications like delivery, search and rescue, and safety inspection especially in low altitude airspace. However, the mass deployment of drones for commercial purposes is yet to be matured. Therefore, normally drone is used in time-critical applications like the delivery of essential medical supplies, these applications often require high reliability. Nowadays, drone normally relies on Global Positioning System (GPS) alone for outdoor navigation, but there is also the possibility that the GPS signal is lost due to GPS jamming in the area. This paper provides a solution for drone navigation in an unknown outdoor environment with no GPS signal. The drone’s surrounding environment is perceived via a camera and is constructed into a 3D occupancy grid map, followed by localization of its position. The navigation is formulated as a sequential decision-making problem and modeled using a partially observable Markov decision process (POMDP). The simulation shows the drone can navigate towards the goal by taking a local optimum decision iteratively based on its perceived surrounding environment at each step.en_US
dc.description.sponsorshipCivil Aviation Authority of Singapore (CAAS)en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.rights© 2022 Nanyang Technological University. All rights reserved. This paper was published by the American Institute of Aeronautics and Astronautics, Inc. in Proceedings of AIAA AVIATION 2022 Forum and is made available with permission of Nanyang Technological University.en_US
dc.subjectEngineering::Aeronautical engineering::Air navigationen_US
dc.titlePreliminary study on drone navigation in urban environments using visual odometry and partially observable Monte Carlo planningen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.conferenceAIAA AVIATION 2022 Forumen_US
dc.contributor.researchAir Traffic Management Research Instituteen_US
dc.description.versionSubmitted/Accepted versionen_US
dc.subject.keywordsUnmanned Aerial Vehiclesen_US
dc.citation.conferencelocationChicago, Illinois (Virtual)en_US
dc.description.acknowledgementThis research is supported by the National Research Foundation (NRF), Singapore, and the Civil Aviation Authority of Singapore (CAAS), under the Aviation Transformation Programme (ATP). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of the National Research Foundation, Singapore, or the Civil Aviation Authority of Singapore.en_US
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