Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance
Arthroscopy is a minimally invasive surgical procedure used to diagnose and treat joint problems. The clinical workflow of arthroscopy typically involves inserting an arthroscope into the joint through a small incision, …
3D ReconstructionDepth EstimationNavigateSimultaneous Localization and Mapping+1Direct Multipath-Based SLAM
In future wireless networks, the availability of information on the position of mobile agents and the propagation environment can enable new services and increase the throughput and robustness of communications. Multipat…
PositionSimultaneous Localization and MappingBlinkTrack: Feature Tracking over 100 FPS via Events and Images
Feature tracking is crucial for, structure from motion (SFM), simultaneous localization and mapping (SLAM), object tracking and various computer vision tasks. Event cameras, known for their high temporal resolution and a…
Object TrackingSimultaneous Localization and MappingNeural Implicit Representation for Highly Dynamic LiDAR Mapping and Odometry
Recent advancements in Simultaneous Localization and Mapping (SLAM) have increasingly highlighted the robustness of LiDAR-based techniques. At the same time, Neural Radiance Fields (NeRF) have introduced new possibilitie…
3D Scene ReconstructionNeRFSimultaneous Localization and MappingEvent-based Stereo Depth Estimation: A Survey
Stereopsis has widespread appeal in robotics as it is the predominant way by which living beings perceive depth to navigate our 3D world. Event cameras are novel bio-inspired sensors that detect per-pixel brightness chan…
Depth EstimationNavigateSimultaneous Localization and MappingStereo Depth Estimation+2Exploring the potential of collaborative UAV 3D mapping in Kenyan savanna for wildlife research
UAV-based biodiversity conservation applications have exhibited many data acquisition advantages for researchers. UAV platforms with embedded data processing hardware can support conservation challenges through 3D habita…
Simultaneous Localization and MappingInitialization of Monocular Visual Navigation for Autonomous Agents Using Modified Structure from Small Motion
We propose a standalone monocular visual Simultaneous Localization and Mapping (vSLAM) initialization pipeline for autonomous space robots. Our method, a state-of-the-art factor graph optimization pipeline, extends Struc…
Motion EstimationSimultaneous Localization and MappingVisual NavigationSpectral Graph Theoretic Methods for Enhancing Network Robustness in Robot Localization
This paper addresses the optimization of edge-weighted networks by maximizing algebraic connectivity to enhance network robustness. Motivated by the need for precise robot position estimation in cooperative localization …
Simultaneous Localization and MappingvalidSPAQ-DL-SLAM: Towards Optimizing Deep Learning-based SLAM for Resource-Constrained Embedded Platforms
Optimizing Deep Learning-based Simultaneous Localization and Mapping (DL-SLAM) algorithms is essential for efficient implementation on resource-constrained embedded platforms, enabling real-time on-board computation in a…
QuantizationSimultaneous Localization and MappingBundle Adjustment in the Eager Mode
Bundle adjustment (BA) is a critical technique in various robotic applications, such as simultaneous localization and mapping (SLAM), augmented reality (AR), and photogrammetry. BA optimizes parameters such as camera pos…
Deep LearningGPUSimultaneous Localization and MappingP2U-SLAM: A Monocular Wide-FoV SLAM System Based on Point Uncertainty and Pose Uncertainty
This paper presents P2U-SLAM, a visual Simultaneous Localization And Mapping (SLAM) system with a wide Field of View (FoV) camera, which utilizes pose uncertainty and point uncertainty. While the wide FoV enables conside…
Simultaneous Localization and MappingSHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning
The ability of neural networks to perform robotic perception and control tasks such as depth and optical flow estimation, simultaneous localization and mapping (SLAM), and automatic control has led to their widespread ad…
Deep Reinforcement LearningOptical Flow EstimationQ-Learningreinforcement-learning+2Object Depth and Size Estimation using Stereo-vision and Integration with SLAM
Autonomous robots use simultaneous localization and mapping (SLAM) for efficient and safe navigation in various environments. LiDAR sensors are integral in these systems for object identification and localization. Howeve…
object-detectionObject DetectionSimultaneous Localization and MappingTowards Localizing Structural Elements: Merging Geometrical Detection with Semantic Verification in RGB-D Data
RGB-D cameras supply rich and dense visual and spatial information for various robotics tasks such as scene understanding, map reconstruction, and localization. Integrating depth and visual information can aid robots in …
3D Plane Detection3d scene graph generationGraph GenerationPanoptic Segmentation+3Robust Second-order LiDAR Bundle Adjustment Algorithm Using Mean Squared Group Metric
The bundle adjustment (BA) algorithm is a widely used nonlinear optimization technique in the backend of Simultaneous Localization and Mapping (SLAM) systems. By leveraging the co-view relationships of landmarks from mul…
Simultaneous Localization and MappingA Survey on Reinforcement Learning Applications in SLAM
The emergence of mobile robotics, particularly in the automotive industry, introduces a promising era of enriched user experiences and adept handling of complex navigation challenges. The realization of these advancement…
Decision Makingreinforcement-learningReinforcement LearningSimultaneous Localization and Mapping+1Reflex-Based Open-Vocabulary Navigation without Prior Knowledge Using Omnidirectional Camera and Multiple Vision-Language Models
Various robot navigation methods have been developed, but they are mainly based on Simultaneous Localization and Mapping (SLAM), reinforcement learning, etc., which require prior map construction or learning. In this stu…
Robot NavigationSimultaneous Localization and MappingRaNDT SLAM: Radar SLAM Based on Intensity-Augmented Normal Distributions Transform
Rescue robotics sets high requirements to perception algorithms due to the unstructured and potentially vision-denied environments. Pivoting Frequency-Modulated Continuous Wave radars are an emerging sensing modality for…
Indoor LocalizationSimultaneous Localization and MappingLoopSplat: Loop Closure by Registering 3D Gaussian Splats
Simultaneous Localization and Mapping (SLAM) based on 3D Gaussian Splats (3DGS) has recently shown promise towards more accurate, dense 3D scene maps. However, existing 3DGS-based methods fail to address the global consi…
3DGSPoint Cloud RegistrationSimultaneous Localization and MappingCorrAdaptor: Adaptive Local Context Learning for Correspondence Pruning
In the fields of computer vision and robotics, accurate pixel-level correspondences are essential for enabling advanced tasks such as structure-from-motion and simultaneous localization and mapping. Recent correspondence…
Graph LearningSimultaneous Localization and Mapping