Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor Navigation
We present a self-supervised learning approach for the semantic segmentation of lidar frames. Our method is used to train a deep point cloud segmentation architecture without any human annotation. The annotation process …
NavigatePoint Cloud SegmentationSegmentationSelf-Supervised Learning+2Visual place recognition: A survey from deep learning perspective
Visual place recognition has attracted widespread research interest in multiple fields such as computer vision and robotics. Recently, researchers have employed advanced deep learning techniques to tackle this problem. W…
Deep LearningLoop Closure DetectionScene UnderstandingSimultaneous Localization and Mapping+3RISE-SLAM: A Resource-aware Inverse Schmidt Estimator for SLAM
In this paper, we present the RISE-SLAM algorithm for performing visual-inertial simultaneous localization and mapping (SLAM), while improving estimation consistency. Specifically, in order to achieve real-time operation…
Computational EfficiencySimultaneous Localization and MappingSemantic SLAM with Autonomous Object-Level Data Association
It is often desirable to capture and map semantic information of an environment during simultaneous localization and mapping (SLAM). Such semantic information can enable a robot to better distinguish places with similar …
ObjectSemantic SLAMSimultaneous Localization and MappingTask PlanningLandmark and IMU Data Fusion: Systematic Convergence Geometric Nonlinear Observer for SLAM and Velocity Bias
Navigation solutions suitable for cases when both autonomous robot's pose (\textit{i.e}., attitude and position) and its environment are unknown are in great demand. Simultaneous Localization and Mapping (SLAM) fulfills …
PositionSimultaneous Localization and MappingDeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place Recognition
Sequence-based place recognition methods for all-weather navigation are well-known for producing state-of-the-art results under challenging day-night or summer-winter transitions. These systems, however, rely on complex …
Autonomous DrivingAutonomous NavigationAutonomous VehiclesImage Retrieval+12BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View
In this paper, we present BirdSLAM, a novel simultaneous localization and mapping (SLAM) system for the challenging scenario of autonomous driving platforms equipped with only a monocular camera. BirdSLAM tackles challen…
Autonomous DrivingMonocular ReconstructionObject LocalizationSimultaneous Localization and MappingDeep Learning based Monocular Depth Prediction: Datasets, Methods and Applications
Estimating depth from RGB images can facilitate many computer vision tasks, such as indoor localization, height estimation, and simultaneous localization and mapping (SLAM). Recently, monocular depth estimation has obtai…
Deep LearningDepth EstimationDepth PredictionIndoor Localization+2Kimera-Multi: a System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping
We present the first fully distributed multi-robot system for dense metric-semantic Simultaneous Localization and Mapping (SLAM). Our system, dubbed Kimera-Multi, is implemented by a team of robots equipped with visual-i…
Simultaneous Localization and MappingOnline Descriptor Enhancement via Self-Labelling Triplets for Visual Data Association
Object-level data association is central to robotic applications such as tracking-by-detection and object-level simultaneous localization and mapping. While current learned visual data association methods outperform hand…
image-classificationImage ClassificationMulti-Object TrackingObject+2Compositional Scalable Object SLAM
We present a fast, scalable, and accurate Simultaneous Localization and Mapping (SLAM) system that represents indoor scenes as a graph of objects. Leveraging the observation that artificial environments are structured an…
ObjectObject SLAMSimultaneous Localization and MappingPushing the Envelope of Rotation Averaging for Visual SLAM
As an essential part of structure from motion (SfM) and Simultaneous Localization and Mapping (SLAM) systems, motion averaging has been extensively studied in the past years and continues to attract surging research atte…
Robot NavigationSimultaneous Localization and MappingRobust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic Calibration
Combining multiple LiDARs enables a robot to maximize its perceptual awareness of environments and obtain sufficient measurements, which is promising for simultaneous localization and mapping (SLAM). This paper proposes …
Simultaneous Localization and MappingThe RobotSlang Benchmark: Dialog-guided Robot Localization and Navigation
Autonomous robot systems for applications from search and rescue to assistive guidance should be able to engage in natural language dialog with people. To study such cooperative communication, we introduce Robot Simultan…
NavigateSimultaneous Localization and MappingA Two-stage Unsupervised Approach for Low light Image Enhancement
As vision based perception methods are usually built on the normal light assumption, there will be a serious safety issue when deploying them into low light environments. Recently, deep learning based methods have been p…
Image EnhancementLow-Light Image EnhancementSimultaneous Localization and MappingVocal Bursts Valence PredictionSemantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment
The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL). The difficulties are two-fold. The first is the…
Graph MatchingSimultaneous Localization and MappingHomography Estimation with Convolutional Neural Networks Under Conditions of Variance
Planar homography estimation is foundational to many computer vision problems, such as Simultaneous Localization and Mapping (SLAM) and Augmented Reality (AR). However, conditions of high variance confound even the state…
Homography EstimationSimultaneous Localization and MappingInpaintFusion: Incremental RGB-D Inpainting for 3D Scenes
State-of-the-art methods for diminished reality propagate pixel information from a keyframe to subsequent frames for real-time inpainting. However, these approaches produce artifacts, if the scene geometry is not suffici…
global-optimizationImage InpaintingSimultaneous Localization and MappingVideo InpaintingFast and Incremental Loop Closure Detection with Deep Features and Proximity Graphs
In recent years, the robotics community has extensively examined methods concerning the place recognition task within the scope of simultaneous localization and mapping applications.This article proposes an appearance-ba…
Loop Closure DetectionSimultaneous Localization and MappingDual-SLAM: A framework for robust single camera navigation
SLAM (Simultaneous Localization And Mapping) seeks to provide a moving agent with real-time self-localization. To achieve real-time speed, SLAM incrementally propagates position estimates. This makes SLAM fast but also m…
Pose EstimationSimultaneous Localization and Mapping