RT info:eu-repo/semantics/article
T1 Non-linearity analysis of depth and angular indexes for optimal stereo SLAM
A1 Bergasa Pascual, Luis Miguel
A1 Fernández Alcantarilla, Pablo
A1 Schleicher Gómez, David
K1 Extended Kalman filter
K1 Localization
K1 Mapping
K1 Inverse depth parametrization
K1 Non-linearity analysis
K1 2D warping
K1 Electrónica
K1 Electronics
AB In this article, we present a real-time 6DoF egomotion estimation system for indoor environments using a wide-angle stereo camera as the only sensor. The stereo camera is carried in hand by a person walking at normal walking speeds 3–5 km/h. We present the basis for a vision-based system that would assist the navigation of the visually impaired by either providing information about their current position and orientation or guiding them to their destination through different sensing modalities. Our sensor combines two different types of feature parametrization: inverse depth and 3D in order to provide orientation and depth information at the same time. Natural landmarks are extracted from the image and are stored as 3D or inverse depth points, depending on a depth threshold. This depth threshold is used for switching between both parametrizations and it is computed by means of a non-linearity analysis of the stereo sensor. Main steps of our system approach are presented as well as an analysis about the optimal way to calculate the depth threshold. At the moment each landmark is initialized, the normal of the patch surface is computed using the information of the stereo pair. In order to improve long-term tracking, a patch warping is done considering the normal vector information. Some experimental results under indoor environments and conclusions are presented.
PB MDPI
SN 1424-8220
YR 2010
FD 2010-04-26
LK http://hdl.handle.net/10017/43550
UL http://hdl.handle.net/10017/43550
LA eng
NO Ministerio de Ciencia e Innovación
DS MINDS@UW
RD 25-abr-2024