Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
Fast Adaptation Nonlinear Observer for SLAM
The process of simultaneously mapping the environment in three dimensional (3D) space and localizing a moving vehicle's pose (orientation and position) is termed Simultaneous Localization and Mapping (SLAM). SLAM is a co…
PositionSimultaneous Localization and MappingAttention-SLAM: A Visual Monocular SLAM Learning from Human Gaze
This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining a visual saliency model (SalNavNet) with traditional monocular …
Simultaneous Localization and MappingSemantic Segmentation of Surface from Lidar Point Cloud
In the field of SLAM (Simultaneous Localization And Mapping) for robot navigation, mapping the environment is an important task. In this regard the Lidar sensor can produce near accurate 3D map of the environment in the …
Point Cloud SegmentationRobot NavigationSemantic SegmentationSimultaneous Localization and Mapping+1Map-merging Algorithms for Visual SLAM: Feasibility Study and Empirical Evaluation
Simultaneous localization and mapping, especially the one relying solely on video data (vSLAM), is a challenging problem that has been extensively studied in robotics and computer vision. State-of-the-art vSLAM algorithm…
NavigateSimultaneous Localization and MappingEvaluation of the Robustness of Visual SLAM Methods in Different Environments
Determining the position and orientation of a sensor vis-a-vis its surrounding, while simultaneously mapping the environment around that sensor or simultaneous localization and mapping is quickly becoming an important ad…
PositionSimultaneous Localization and MappingAdjusting Bias in Long Range Stereo Matching: A semantics guided approach
Stereo vision generally involves the computation of pixel correspondences and estimation of disparities between rectified image pairs. In many applications, including simultaneous localization and mapping (SLAM) and 3D o…
3D Object DetectionAutonomous NavigationDepth EstimationDisparity Estimation+4DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features
A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for robot autonomy. For visual SLAM algorithms, though the theoretical framework has been well established for most aspects, feature…
GPULoop Closure DetectionSimultaneous Localization and MappingIV-SLAM: Introspective Vision for Simultaneous Localization and Mapping
Existing solutions to visual simultaneous localization and mapping (V-SLAM) assume that errors in feature extraction and matching are independent and identically distributed (i.i.d), but this assumption is known to not b…
Simultaneous Localization and MappingVariational Filtering with Copula Models for SLAM
The ability to infer map variables and estimate pose is crucial to the operation of autonomous mobile robots. In most cases the shared dependency between these variables is modeled through a multivariate Gaussian distrib…
Simultaneous Localization and MappingRotational Outlier Identification in Pose Graphs Using Dual Decomposition
In the last few years, there has been an increasing trend to consider Structure from Motion (SfM, in computer vision) and Simultaneous Localization and Mapping (SLAM, in robotics) problems from the point of view of pose …
Outlier DetectionSimultaneous Localization and MappingDeep Depth Estimation from Visual-Inertial SLAM
This paper addresses the problem of learning to complete a scene's depth from sparse depth points and images of indoor scenes. Specifically, we study the case in which the sparse depth is computed from a visual-inertial …
Depth EstimationSimultaneous Localization and MappingA SLAM Map Restoration Algorithm Based on Submaps and an Undirected Connected Graph
Many visual simultaneous localization and mapping (SLAM) systems have been shown to be accurate and robust, and have real-time performance capabilities on both indoor and ground datasets. However, these methods can be pr…
Simultaneous Localization and MappingOnline Visual Place Recognition via Saliency Re-identification
As an essential component of visual simultaneous localization and mapping (SLAM), place recognition is crucial for robot navigation and autonomous driving. Existing methods often formulate visual place recognition as fea…
Autonomous DrivingRobot NavigationSaliency DetectionSimultaneous Localization and Mapping+1Deep Keypoint-Based Camera Pose Estimation with Geometric Constraints
Estimating relative camera poses from consecutive frames is a fundamental problem in visual odometry (VO) and simultaneous localization and mapping (SLAM), where classic methods consisting of hand-crafted features and sa…
Camera Pose EstimationPose EstimationSimultaneous Localization and MappingVisual OdometryEndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner
Deep learning techniques hold promise to develop dense topography reconstruction and pose estimation methods for endoscopic videos. However, currently available datasets do not support effective quantitative benchmarking…
BenchmarkingDepth EstimationMonocular Visual OdometryPose Estimation+3Exploiting Diffuse Multipath in 5G SLAM
5G millimeter wave (mmWave) signals can be used to jointly localize the receiver and map the propagation environment in vehicular networks, which is a typical simultaneous localization and mapping (SLAM) problem. Mapping…
Simultaneous Localization and MappingCPL-SLAM: Efficient and Certifiably Correct Planar Graph-Based SLAM Using the Complex Number Representation
In this paper, we consider the problem of planar graph-based simultaneous localization and mapping (SLAM) that involves both poses of the autonomous agent and positions of observed landmarks. We present CPL-SLAM, an effi…
C++ codeSimultaneous Localization and MappingGMMLoc: Structure Consistent Visual Localization with Gaussian Mixture Models
Incorporating prior structure information into the visual state estimation could generally improve the localization performance. In this letter, we aim to address the paradox between accuracy and efficiency in coupling v…
Simultaneous Localization and MappingState EstimationVisual LocalizationA Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence
Deep learning based localization and mapping has recently attracted significant attention. Instead of creating hand-designed algorithms through exploitation of physical models or geometric theories, deep learning based s…
Deep LearningScene UnderstandingSimultaneous Localization and MappingRevisiting visual-inertial structure from motion for odometry and SLAM initialization
In this paper, an efficient closed-form solution for the state initialization in visual-inertial odometry (VIO) and simultaneous localization and mapping (SLAM) is presented. Unlike the state-of-the-art, we do not derive…
Simultaneous Localization and Mapping