Direct Depth SLAM: Sparse Geometric Feature Enhanced Direct Depth SLAM System for Low-Texture Environments
نویسندگان
چکیده
منابع مشابه
Efficient Feature Parameterisation for Visual SLAM Using Inverse Depth Bundles
Flexibility and robustness of visual SLAM systems have been shown to benefit from an inverse depth parameterisation of features. However the increased number of 6 parameters per feature presents a problem to real-time EKF SLAM implementations because their computational complexity scales quadratically with the size of the state vector. Recent work tackles this for instance by converting the rep...
متن کاملLSD-SLAM: Large-Scale Direct Monocular SLAM
We propose a direct (feature-less) monocular SLAM algorithm which, in contrast to current state-of-the-art regarding direct methods, allows to build large-scale, consistent maps of the environment. Along with highly accurate pose estimation based on direct image alignment, the 3D environment is reconstructed in real-time as pose-graph of keyframes with associated semi-dense depth maps. These ar...
متن کاملDelayed Inverse Depth Monocular SLAM
The 6-DOF monocular camera case possibly represents the harder variant in the context of simultaneous localization and mapping problem. In the last years, several advances have been appeared in this area; however the application of these techniques to real world applications it’s difficult so far. Recently, the unified inverse depth parametrization has shown to be a good option this challenging...
متن کاملUnified Inverse Depth Parametrization for Monocular SLAM
Recent work has shown that the probabilistic SLAM approach of explicit uncertainty propagation can succeed in permitting repeatable 3D real-time localization and mapping even in the ‘pure vision’ domain of a single agile camera with no extra sensing. An issue which has caused difficulty in monocular SLAM however is the initialization of features, since information from multiple images acquired ...
متن کاملPop-up SLAM: a Semantic Monocular Plane SLAM for Low-texture Environments
Existing simultaneous localization and mapping (SLAM) algorithm is not robust in challenging low-texture environments because of few salient features. The resulting sparse or semi-dense map also conveys little information for motion planning. Though some work utilize plane or scene layout for dense map regularization, they require decent state estimation from other sources. In this paper, we pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2018
ISSN: 1424-8220
DOI: 10.3390/s18103339