Localização e mapeamento simultâneos de ambientes planos usando visão monocular e representação híbrida do ambiente
The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping) solution based on Extended Kalman Filter (EKF) in order to make possible a robot navigates along the environment using information from odometry and pre-existing lines on the floor. Initially, a segmentation step i...
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| Format: | doctoralThesis |
| Language: | por |
| Published: |
Universidade Federal do Rio Grande do Norte
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| Online Access: | https://repositorio.ufrn.br/jspui/handle/123456789/15150 |
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| Summary: | The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping)
solution based on Extended Kalman Filter (EKF) in order to make possible a robot
navigates along the environment using information from odometry and pre-existing lines
on the floor. Initially, a segmentation step is necessary to classify parts of the image in
floor or non floor . Then the image processing identifies floor lines and the parameters
of these lines are mapped to world using a homography matrix. Finally, the identified
lines are used in SLAM as landmarks in order to build a feature map.
In parallel, using the corrected robot pose, the uncertainty about the pose and also the
part non floor of the image, it is possible to build an occupancy grid map and generate
a metric map with the obstacle s description.
A greater autonomy for the robot is attained by using the two types of obtained map
(the metric map and the features map). Thus, it is possible to run path planning tasks in
parallel with localization and mapping.
Practical results are presented to validate the proposal |
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