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- W2319945170 abstract "The objective of this study is developing a visual simultaneous localization and mapping (vSLAM) system using a monocular vision. The vSLAM system could provide the aerial robot the capabilities of autonomous navigation in global positioning system (GPS) denied environments. When the aerial robot navigates in a GPS-denied environment, the vSLAM system collects the measurement information for robot state estimation and environmental mapping. Considering the carrying capacity of the aerial robot, a single camera is used in this study and the image is transmitted to PC-based controller for image processing. The extended Kalman filter is used as the state estimator to recursively predict and update the states of the aerial robot and the environment landmarks. The map scale determination problem of monocular vision is solved by using a one-dimensional ultrasonic distance sensor. Meanwhile, the image depth is represented by using the inverse depth parameterization method and the image features initialization is achieved by a non-delayed procedure. The robot vSLAM system integrates the sensor inputs, image processing, and state estimation. The resultant system is used to perform the tasks of simultaneous localization and mapping for aerial robots." @default.
- W2319945170 created "2016-06-24" @default.
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- W2319945170 date "2015-01-01" @default.
- W2319945170 modified "2023-10-16" @default.
- W2319945170 title "Aerial Robot Simultaneous Localization and Mapping with a Monocular Vision" @default.
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- W2319945170 doi "https://doi.org/10.12792/icisip2015.040" @default.
- W2319945170 hasPublicationYear "2015" @default.
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