Papers Loop Closure Detection
“Loop Closure Detection” 태그가 달린 논문 89편 · 필터 해제
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR
Millimeter-wave (mmWave) 5G New Radio (NR) communication systems, with their high-resolution antenna arrays and extensive bandwidth, offer a transformative opportunity for high-throughput data transmission and advanced e…
Loop Closure DetectionPoint Cloud GenerationPoint Cloud RegistrationSimultaneous Localization and MappingVisual Loop Closure Detection Through Deep Graph Consensus
Visual loop closure detection traditionally relies on place recognition methods to retrieve candidate loops that are validated using computationally expensive RANSAC-based geometric verification. As false positive loop c…
Computational EfficiencyGraph Neural NetworkLoop Closure DetectionSimultaneous Localization and MappingImproved Bag-of-Words Image Retrieval with Geometric Constraints for Ground Texture Localization
Ground texture localization using a downward-facing camera offers a low-cost, high-precision localization solution that is robust to dynamic environments and requires no environmental modification. We present a significa…
Image RetrievalLoop Closure DetectionPNE-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 MappingForestLPR: LiDAR Place Recognition in Forests Attentioning Multiple BEV Density Images
Place recognition is essential to maintain global consistency in large-scale localization systems. While research in urban environments has progressed significantly using LiDARs or cameras, applications in natural forest…
3D Place RecognitionLoop Closure DetectionSLAM in the Dark: Self-Supervised Learning of Pose, Depth and Loop-Closure from Thermal Images
Visual SLAM is essential for mobile robots, drone navigation, and VR/AR, but traditional RGB camera systems struggle in low-light conditions, driving interest in thermal SLAM, which excels in such environments. However, …
Depth EstimationDrone navigationLoop Closure DetectionSelf-Supervised Learning+1LiDAR Loop Closure Detection using Semantic Graphs with Graph Attention Networks
In this paper, we propose a novel loop closure detection algorithm that uses graph attention neural networks to encode semantic graphs to perform place recognition and then use semantic registration to estimate the 6 DoF…
Graph AttentionGraph EmbeddingLoop Closure DetectionVINGS-Mono: Visual-Inertial Gaussian Splatting Monocular SLAM in Large Scenes
VINGS-Mono is a monocular (inertial) Gaussian Splatting (GS) SLAM framework designed for large scenes. The framework comprises four main components: VIO Front End, 2D Gaussian Map, NVS Loop Closure, and Dynamic Eraser. I…
Loop Closure DetectionNeRFNovel View SynthesisBalancing Accuracy and Efficiency for Large-Scale SLAM: A Minimal Subset Approach for Scalable Loop Closures
Typical LiDAR SLAM architectures feature a front-end for odometry estimation and a back-end for refining and optimizing the trajectory and map, commonly through loop closures. However, loop closure detection in large-sca…
global-optimizationLoop Closure DetectionExploring Emerging Trends and Research Opportunities in Visual Place Recognition
Visual-based recognition, e.g., image classification, object detection, etc., is a long-standing challenge in computer vision and robotics communities. Concerning the roboticists, since the knowledge of the environment i…
image-classificationImage ClassificationLoop Closure Detectionobject-detection+3Why Sample Space Matters: Keyframe Sampling Optimization for LiDAR-based Place Recognition
Recent advances in robotics are driving real-world autonomy for long-term and large-scale missions, where loop closures via place recognition are vital for mitigating pose estimation drift. However, achieving real-time p…
Loop Closure DetectionPose EstimationOpen-Set Semantic Uncertainty Aware Metric-Semantic Graph Matching
Underwater object-level mapping requires incorporating visual foundation models to handle the uncommon and often previously unseen object classes encountered in marine scenarios. In this work, a metric of semantic uncert…
Graph MatchingLoop Closure DetectionObjectAppearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation
In appearance-based localization and mapping, loop closure detection is the process used to determinate if the current observation comes from a previously visited location or a new one. As the size of the internal map in…
Loop Closure DetectionMemory Management for Real-Time Appearance-Based Loop Closure Detection
Loop closure detection is the process involved when trying to find a match between the current and a previously visited locations in SLAM. Over time, the amount of time required to process new observations increases with…
Loop Closure DetectionManagementGV-Bench: Benchmarking Local Feature Matching for Geometric Verification of Long-term Loop Closure Detection
Visual loop closure detection is an important module in visual simultaneous localization and mapping (SLAM), which associates current camera observation with previously visited places. Loop closures correct drifts in tra…
BenchmarkingLoop Closure DetectionPose EstimationSimultaneous Localization and Mapping+1OverlapMamba: Novel Shift State Space Model for LiDAR-based Place Recognition
Place recognition is the foundation for enabling autonomous systems to achieve independent decision-making and safe operations. It is also crucial in tasks such as loop closure detection and global localization within SL…
Decision MakingLoop Closure DetectionMambaState Space ModelsMoD-SLAM: Monocular Dense Mapping for Unbounded 3D Scene Reconstruction
Monocular SLAM has received a lot of attention due to its simple RGB inputs and the lifting of complex sensor constraints. However, existing monocular SLAM systems are designed for bounded scenes, restricting the applica…
3D Reconstruction3D Scene ReconstructionDepth EstimationLoop Closure Detection+4DK-SLAM: Monocular Visual SLAM with Deep Keypoint Learning, Tracking and Loop-Closing
The performance of visual SLAM in complex, real-world scenarios is often compromised by unreliable feature extraction and matching when using handcrafted features. Although deep learning-based local features excel at cap…
Loop Closure DetectionMeta-LearningPose EstimationDDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM
SLAM systems based on NeRF have demonstrated superior performance in rendering quality and scene reconstruction for static environments compared to traditional dense SLAM. However, they encounter tracking drift and mappi…
Loop Closure DetectionNeRFOptical Flow EstimationSemantic SLAMAttacking the Loop: Adversarial Attacks on Graph-based Loop Closure Detection
With the advancement in robotics, it is becoming increasingly common for large factories and warehouses to incorporate visual SLAM (vSLAM) enabled automated robots that operate closely next to humans. This makes any adve…
Loop Closure Detection