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Monocular visual SLAM for small UAVs in GPS-denied environments

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Abstract

This paper presents a monocular visual simultaneous localization and mapping (SLAM) system for a small unmanned aerial vehicle (UAV) in GPS-denied environments. A single camera is used to measure the motion of the vehicle and detect features (landmarks) for the map building. The SLAM estimates the positions of the UAV and the features by an extended Kalman filter (EKF), which takes the velocity estimated by the fusion of the inertial and visual measurements as the input. An inverse depth method is adopted for the feature initialization. Both simulations and experiments are carried out to verify the effectiveness of this system.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest
Pages896-901
Number of pages6
DOIs
StatePublished - 2012
Event2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Guangzhou, China
Duration: 11 Dec 201214 Dec 2012

Publication series

Name2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest

Conference

Conference2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012
Country/TerritoryChina
CityGuangzhou
Period11/12/1214/12/12

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