Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
TagSLAM: Robust SLAM with Fiducial Markers
TagSLAM provides a convenient, flexible, and robust way of performing Simultaneous Localization and Mapping (SLAM) with AprilTag fiducial markers. By leveraging a few simple abstractions (bodies, tags, cameras), TagSLAM …
Camera CalibrationPose EstimationSimultaneous Localization and MappingVisual LocalizationHierarchical Encoding of Sequential Data With Compact and Sub-Linear Storage Cost
Snapshot-based visual localization is an important problem in several computer vision and robotics applications such as Simultaneous Localization And Mapping (SLAM). To achieve real-time performance in very large-scale …
QuantizationSimultaneous Localization and MappingVisual LocalizationActive collaboration in relative observation for Multi-agent visual SLAM based on Deep Q Network
This paper proposes a unique active relative localization mechanism for multi-agent Simultaneous Localization and Mapping(SLAM),in which a agent to be observed are considered as a task, which is performed by others assis…
Deep Reinforcement LearningReinforcement LearningSimultaneous Localization and MappingKalman Filtering with Gaussian Processes Measurement Noise
Real-world measurement noise in applications like robotics is often correlated in time, but we typically assume i.i.d. Gaussian noise for filtering. We propose general Gaussian Processes as a non-parametric model for cor…
Gaussian ProcessesSimultaneous Localization and MappingA Fast and Robust Place Recognition Approach for Stereo Visual Odometry Using LiDAR Descriptors
Place recognition is a core component of Simultaneous Localization and Mapping (SLAM) algorithms. Particularly in visual SLAM systems, previously-visited places are recognized by measuring the appearance similarity betwe…
Computational EfficiencySimultaneous Localization and MappingVisual OdometrySE-SLAM: Semi-Dense Structured Edge-Based Monocular SLAM
Vision-based Simultaneous Localization And Mapping (VSLAM) is a mature problem in Robotics. Most VSLAM systems are feature based methods, which are robust and present high accuracy, but yield sparse maps with limited app…
Simultaneous Localization and MappingminiSAM: A Flexible Factor Graph Non-linear Least Squares Optimization Framework
Many problems in computer vision and robotics can be phrased as non-linear least squares optimization problems represented by factor graphs, for example, simultaneous localization and mapping (SLAM), structure from motio…
BenchmarkingMotion PlanningSimultaneous Localization and MappingLiDARTag: A Real-Time Fiducial Tag System for Point Clouds
Image-based fiducial markers are useful in problems such as object tracking in cluttered or textureless environments, camera (and multi-sensor) calibration tasks, and vision-based simultaneous localization and mapping (S…
Object TrackingSensor FusionSimultaneous Localization and MappingTAGHow far should self-driving cars see? Effect of observation range on vehicle self-localization
Accuracy and time efficiency are two essential requirements for the self-localization of autonomous vehicles. While the observation range considered for simultaneous localization and mapping (SLAM) has a significant effe…
Autonomous DrivingAutonomous VehiclesSelf-Driving CarsSimultaneous Localization and MappingHybrid Camera Pose Estimation with Online Partitioning for SLAM
This paper presents a hybrid real-time camera pose estimation framework with a novel partitioning scheme and introduces motion averaging to monocular Simultaneous Localization and Mapping (SLAM) systems. Breaking through…
Camera Pose EstimationPose EstimationSimultaneous Localization and MappingDegeneracy in Self-Calibration Revisited and a Deep Learning Solution for Uncalibrated SLAM
Self-calibration of camera intrinsics and radial distortion has a long history of research in the computer vision community. However, it remains rare to see real applications of such techniques to modern Simultaneous Loc…
Simultaneous Localization and MappingNot Only Look But Observe: Variational Observation Model of Scene-Level 3D Multi-Object Understanding for Probabilistic SLAM
We present NOLBO, a variational observation model estimation for 3D multi-object from 2D single shot. Previous probabilistic instance-level understandings mainly consider the single-object image, not single shot with mul…
ObjectSimultaneous Localization and MappingReal-time Vision-based Depth Reconstruction with NVidia Jetson
Vision-based depth reconstruction is a challenging problem extensively studied in computer vision but still lacking universal solution. Reconstructing depth from single image is particularly valuable to mobile robotics a…
Simultaneous Localization and MappingSegway DRIVE Benchmark: Place Recognition and SLAM Data Collected by A Fleet of Delivery Robots
Visual place recognition and simultaneous localization and mapping (SLAM) have recently begun to be used in real-world autonomous navigation tasks like food delivery. Existing datasets for SLAM research are often not rep…
Autonomous NavigationSimultaneous Localization and MappingVisual Place RecognitionDynamic-SLAM: Semantic monocular visual localization and mapping based on deep learning in dynamic environment
When working in dynamic environment, traditional SLAM framework performs poorly due to interference from dynamic objects. By taking advantages of deep learning in object detection, a semantic simultaneous localization an…
object-detectionObject DetectionPose EstimationSemantic SLAM+2SLAM Endoscopy enhanced by adversarial depth prediction
Medical endoscopy remains a challenging application for simultaneous localization and mapping (SLAM) due to the sparsity of image features and size constraints that prevent direct depth-sensing. We present a SLAM approac…
Depth EstimationDepth PredictionMonocular Depth EstimationPrediction+1PyRobot: An Open-source Robotics Framework for Research and Benchmarking
This paper introduces PyRobot, an open-source robotics framework for research and benchmarking. PyRobot is a light-weight, high-level interface on top of ROS that provides a consistent set of hardware independent mid-lev…
BenchmarkingRobotic GraspingRobot NavigationSimultaneous Localization and MappingMovable-Object-Aware Visual SLAM via Weakly Supervised Semantic Segmentation
Moving objects can greatly jeopardize the performance of a visual simultaneous localization and mapping (vSLAM) system which relies on the static-world assumption. Motion removal have seen successful on solving this prob…
SegmentationSemantic SegmentationSimultaneous Localization and MappingWeakly supervised Semantic Segmentation+1Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images
Depth perception is a key component for autonomous systems that interact in the real world, such as delivery robots, warehouse robots, and self-driving cars. Tasks in autonomous robotics such as 3D object recognition, si…
3D Object RecognitionGenerative Adversarial NetworkObject RecognitionSelf-Driving Cars+1eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platform
Simultaneous Localization and Mapping (SLAM) is a critical task for autonomous navigation. However, due to the computational complexity of SLAM algorithms, it is very difficult to achieve real-time implementation on low-…
Autonomous NavigationSimultaneous Localization and Mapping