Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
BAD SLAM: Bundle Adjusted Direct RGB-D SLAM
A key component of Simultaneous Localization and Mapping (SLAM) systems is the joint optimization of the estimated 3D map and camera trajectory. Bundle adjustment (BA) is the gold standard for this. Due to the large numb…
Simultaneous Localization and MappingDirect Sparse Mapping
Photometric bundle adjustment, PBA, accurately estimates geometry from video. However, current PBA systems have a temporary map that cannot manage scene reobservations. We present, DSM, a full monocular visual SLAM based…
Simultaneous Localization and MappingContinuous Direct Sparse Visual Odometry from RGB-D Images
This paper reports on a novel formulation and evaluation of visual odometry from RGB-D images. Assuming a static scene, the developed theoretical framework generalizes the widely used direct energy formulation (photometr…
Simultaneous Localization and MappingVisual OdometrySpiking Neural Network on Neuromorphic Hardware for Energy-Efficient Unidimensional SLAM
Energy-efficient simultaneous localization and mapping (SLAM) is crucial for mobile robots exploring unknown environments. The mammalian brain solves SLAM via a network of specialized neurons, exhibiting asynchronous com…
Bayesian InferenceCPUSimultaneous Localization and MappingIncremental Visual-Inertial 3D Mesh Generation with Structural Regularities
Visual-Inertial Odometry (VIO) algorithms typically rely on a point cloud representation of the scene that does not model the topology of the environment. A 3D mesh instead offers a richer, yet lightweight, model. Nevert…
3D ReconstructionSimultaneous Localization and MappingState EstimationSparse Depth Enhanced Direct Thermal-infrared SLAM Beyond the Visible Spectrum
In this paper, we propose a thermal-infrared simultaneous localization and mapping (SLAM) system enhanced by sparse depth measurements from Light Detection and Ranging (LiDAR). Thermal-infrared cameras are relatively rob…
Motion EstimationSimultaneous Localization and MappingBeyond Photometric Loss for Self-Supervised Ego-Motion Estimation
Accurate relative pose is one of the key components in visual odometry (VO) and simultaneous localization and mapping (SLAM). Recently, the self-supervised learning framework that jointly optimizes the relative pose and …
Camera Pose EstimationMotion EstimationSelf-Supervised LearningSimultaneous Localization and Mapping+1GSLAM: A General SLAM Framework and Benchmark
SLAM technology has recently seen many successes and attracted the attention of high-technological companies. However, how to unify the interface of existing or emerging algorithms, and effectively perform benchmark abou…
Simultaneous Localization and MappingUcoSLAM: Simultaneous Localization and Mapping by Fusion of KeyPoints and Squared Planar Markers
This paper proposes a novel approach for Simultaneous Localization and Mapping by fusing natural and artificial landmarks. Most of the SLAM approaches use natural landmarks (such as keypoints). However, they are unstable…
Simultaneous Localization and MappingGEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping
We present a Deep Learning based system for the twin tasks of localization and obstacle avoidance essential to any mobile robot. Our system learns from conventional geometric SLAM, and outputs, using a single camera, the…
Depth EstimationSimultaneous Localization and MappingDF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features
As the foundation of driverless vehicle and intelligent robots, Simultaneous Localization and Mapping(SLAM) has attracted much attention these days. However, non-geometric modules of traditional SLAM algorithms are limit…
GPUSimultaneous Localization and Mapping3D Scene Parsing via Class-Wise Adaptation
We propose the method that uses only computer graphics datasets to parse the real world 3D scenes. 3D scene parsing based on semantic segmentation is required to implement the categorical interaction in the virtual world…
Scene ParsingSegmentationSemantic SegmentationSimultaneous Localization and MappingReal-time Indoor Scene Reconstruction with RGBD and Inertia Input
Camera motion estimation is a key technique for 3D scene reconstruction and Simultaneous localization and mapping (SLAM). To make it be feasibly achieved, previous works usually assume slow camera motions, which limits i…
3D Reconstruction3D Scene ReconstructionIndoor Scene ReconstructionMotion Estimation+1Network Uncertainty Informed Semantic Feature Selection for Visual SLAM
In order to facilitate long-term localization using a visual simultaneous localization and mapping (SLAM) algorithm, careful feature selection can help ensure that reference points persist over long durations and the run…
feature selectionSemantic SegmentationSimultaneous Localization and MappingVisual OdometryLoop Closure Detection with RGB-D Feature Pyramid Siamese Networks
In visual Simultaneous Localization And Mapping (SLAM), detecting loop closures has been an important but difficult task. Currently, most solutions are based on the bag-of-words approach. Yet the possibility of deep neur…
Loop Closure DetectionSimultaneous Localization and MappingJoint Range and Angle Estimation for FMCW MIMO Radar and Its Application
Recently, frequency-modulated continuous wave (FMCW) radars with array antennas are gaining in popularity on a wide variety of commercial applications. A usual approach of the range and angle estimation of a target with …
Simultaneous Localization and MappingRGB-D SLAM in Dynamic Environments Using Point Correlations
In this paper, a simultaneous localization and mapping (SLAM) method that eliminates the influence of moving objects in dynamic environments is proposed. This method utilizes the correlation between map points to separat…
Motion EstimationSimultaneous Localization and MappingSemi-Semantic Line-Cluster Assisted Monocular SLAM for Indoor Environments
This paper presents a novel method to reduce the scale drift for indoor monocular simultaneous localization and mapping (SLAM). We leverage the prior knowledge that in the indoor environment, the line segments form tight…
Simultaneous Localization and MappingLocalization and Perception for Control and Decision Making of a Low Speed Autonomous Shuttle in a Campus Pilot Deployment
Future SAE Level 4 and Level 5 autonomous vehicles will require novel applications of localization, perception, control and artificial intelligence technology in order to offer innovative and disruptive solutions to curr…
Autonomous DrivingAutonomous VehiclesDecision MakingSelf-Driving Cars+1Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations
Most problems involving simultaneous localization and mapping can nowadays be solved using one of two fundamentally different approaches. The traditional approach is given by a least-squares objective, which minimizes ma…
Object ReconstructionSimultaneous Localization and Mapping