Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment
In battlefield environments, adversaries frequently disrupt GPS signals, requiring alternative localization and navigation methods. Traditional vision-based approaches like Simultaneous Localization and Mapping (SLAM) an…
Sensor FusionSimultaneous Localization and MappingVisual LocalizationVisual OdometryEdgePoint2: Compact Descriptors for Superior Efficiency and Accuracy
The field of keypoint extraction, which is essential for vision applications like Structure from Motion (SfM) and Simultaneous Localization and Mapping (SLAM), has evolved from relying on handcrafted methods to leveragin…
Edge-computingKeypoint DetectionSimultaneous Localization and MappingDERD-Net: Learning Depth from Event-based Ray Densities
Event cameras offer a promising avenue for multi-view stereo depth estimation and Simultaneous Localization And Mapping (SLAM) due to their ability to detect blur-free 3D edges at high-speed and over broad illumination c…
Depth EstimationDepth PredictionSimultaneous Localization and MappingStereo Depth EstimationSLAM&Render: A Benchmark for the Intersection Between Neural Rendering, Gaussian Splatting and SLAM
Models and methods originally developed for novel view synthesis and scene rendering, such as Neural Radiance Fields (NeRF) and Gaussian Splatting, are increasingly being adopted as representations in Simultaneous Locali…
NeRFNeural RenderingNovel View SynthesisSimultaneous Localization and MappingPNE-SGAN: Probabilistic NDT-Enhanced Semantic Graph Attention Network for LiDAR Loop Closure Detection
LiDAR loop closure detection (LCD) is crucial for consistent Simultaneous Localization and Mapping (SLAM) but faces challenges in robustness and accuracy. Existing methods, including semantic graph approaches, often suff…
Graph AttentionGraph SimilarityLoop Closure DetectionSimultaneous Localization and MappingEmbracing Dynamics: Dynamics-aware 4D Gaussian Splatting SLAM
Simultaneous localization and mapping (SLAM) technology now has photorealistic mapping capabilities thanks to the real-time high-fidelity rendering capability of 3D Gaussian splatting (3DGS). However, due to the static r…
3DGSPose TrackingSimultaneous Localization and MappingVSLAM-LAB: A Comprehensive Framework for Visual SLAM Methods and Datasets
Visual Simultaneous Localization and Mapping (VSLAM) research faces significant challenges due to fragmented toolchains, complex system configurations, and inconsistent evaluation methodologies. To address these issues, …
Simultaneous Localization and MappingNonlinear Observer Design for Landmark-Inertial Simultaneous Localization and Mapping
This paper addresses the problem of Simultaneous Localization and Mapping (SLAM) for rigid body systems in three-dimensional space. We introduce a new matrix Lie group SE_{3+n}(3), whose elements are composed of the pose…
PositionSimultaneous Localization and MappingMultimodal Fusion and Vision-Language Models: A Survey for Robot Vision
Robot vision has greatly benefited from advancements in multimodal fusion techniques and vision-language models (VLMs). We systematically review the applications of multimodal fusion in key robotic vision tasks, includin…
3D Object Detectioncross-modal alignmentDomain Adaptationobject-detection+5MonoGS++: Fast and Accurate Monocular RGB Gaussian SLAM
We present MonoGS++, a novel fast and accurate Simultaneous Localization and Mapping (SLAM) method that leverages 3D Gaussian representations and operates solely on RGB inputs. While previous 3D Gaussian Splatting (GS)-b…
3D Scene ReconstructionSimultaneous Localization and MappingVisual OdometrySTAMICS: Splat, Track And Map with Integrated Consistency and Semantics for Dense RGB-D SLAM
Simultaneous Localization and Mapping (SLAM) is a critical task in robotics, enabling systems to autonomously navigate and understand complex environments. Current SLAM approaches predominantly rely on geometric cues for…
Camera Pose EstimationNavigatePose EstimationSimultaneous Localization and MappingGI-SLAM: Gaussian-Inertial SLAM
3D Gaussian Splatting (3DGS) has recently emerged as a powerful representation of geometry and appearance for dense Simultaneous Localization and Mapping (SLAM). Through rapid, differentiable rasterization of 3D Gaussian…
3DGSSimultaneous Localization and MappingA Sigma Point-based Low Complexity Algorithm for Multipath-based SLAM in MIMO Systems
Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising approach in wireless networks to jointly obtain position information of transmitters/receivers and information of the propagation environment…
Simultaneous Localization and Mapping3D Densification for Multi-Map Monocular VSLAM in Endoscopy
Multi-map Sparse Monocular visual Simultaneous Localization and Mapping applied to monocular endoscopic sequences has proven efficient to robustly recover tracking after the frequent losses in endoscopy due to motion blu…
Camera LocalizationDepth EstimationMonocular Depth EstimationSimultaneous Localization and MappingDynaGSLAM: Real-Time Gaussian-Splatting SLAM for Online Rendering, Tracking, Motion Predictions of Moving Objects in Dynamic Scenes
Simultaneous Localization and Mapping (SLAM) is one of the most important environment-perception and navigation algorithms for computer vision, robotics, and autonomous cars/drones. Hence, high quality and fast mapping b…
3DGSSimultaneous Localization and MappingAQUA-SLAM: Tightly-Coupled Underwater Acoustic-Visual-Inertial SLAM with Sensor Calibration
Underwater environments pose significant challenges for visual Simultaneous Localization and Mapping (SLAM) systems due to limited visibility, inadequate illumination, and sporadic loss of structural features in images. …
Simultaneous Localization and MappingDVM-SLAM: Decentralized Visual Monocular Simultaneous Localization and Mapping for Multi-Agent Systems
Cooperative Simultaneous Localization and Mapping (C-SLAM) enables multiple agents to work together in mapping unknown environments while simultaneously estimating their own positions. This approach enhances robustness, …
Autonomous NavigationCollision AvoidanceSimultaneous Localization and MappingOn the Connection Between Magnetic-Field Odometry Aided Inertial Navigation and Magnetic-Field SLAM
Magnetic-field simultaneous localization and mapping (SLAM) using consumer-grade inertial and magnetometer sensors offers a scalable, cost-effective solution for indoor localization. However, the rapid error accumulation…
Indoor LocalizationSimultaneous Localization and MappingInclusive STEAM Education: A Framework for Teaching Cod-2 ing and Robotics to Students with Visually Impairment Using 3 Advanced Computer Vision
STEAM education integrates Science, Technology, Engineering, Arts, and Mathematics to foster creativity and problem-solving. However, students with visual impairments (VI) encounter significant challenges in programming …
Simultaneous Localization and MappingMonocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines
With the rise of deep learning, there is a fundamental change in visual SLAM algorithms toward developing different modules trained as end-to-end pipelines. However, regardless of the implementation domain, visual SLAM's…
Simultaneous Localization and Mapping