ReviewSensors (Basel, Switzerland)2022
Visual SLAM: What Are the Current Trends and What to Expect?
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
22 citing papers in PubMed.
- DUDG-SLAM: Dynamic Replay and Depth-Uncertainty-Guided Gaussian SLAM for Robust RGB-D Reconstruction.Sensors (Basel, Switzerland) · 2026Article
- Video-Based 3D Reconstruction: A Review of Photogrammetry and Visual SLAM Approaches.Journal of imaging · 2026Review
- Online Mapping from Weight Matching Odometry and Highly Dynamic Point Cloud Filtering via Pseudo-Occupancy Grid.Sensors (Basel, Switzerland) · 2025Article
- Semantic Fusion Algorithm of 2D LiDAR and Camera Based on Contour and Inverse Projection.Sensors (Basel, Switzerland) · 2025Article
- Monocular Initialization for Real-Time Feature-Based SLAM in Dynamic Environments with Multiple Frames.Sensors (Basel, Switzerland) · 2025Article
- Parallelized SLAM: Enhancing Mapping and Localization Through Concurrent Processing.Sensors (Basel, Switzerland) · 2025Article
- ecg2o: a seamless extension of g2o for equality-constrained factor graph optimization.Frontiers in robotics and AI · 2025Article
- DIO-SLAM: A Dynamic RGB-D SLAM Method Combining Instance Segmentation and Optical Flow.Sensors (Basel, Switzerland) · 2024Article
- Application of Event Cameras and Neuromorphic Computing to VSLAM: A Survey.Biomimetics (Basel, Switzerland) · 2024Review
- DSOMF: A Dynamic Environment Simultaneous Localization and Mapping Technique Based on Machine Learning.Sensors (Basel, Switzerland) · 2024Article
- Visual SLAM for Unmanned Aerial Vehicles: Localization and Perception.Sensors (Basel, Switzerland) · 2024Review
- An Audio-Based SLAM for Indoor Environments: A Robotic Mixed Reality Presentation.Sensors (Basel, Switzerland) · 2024Article
- LRPL-VIO: A Lightweight and Robust Visual-Inertial Odometry with Point and Line Features.Sensors (Basel, Switzerland) · 2024Article
- A Review of Sensing Technologies for Indoor Autonomous Mobile Robots.Sensors (Basel, Switzerland) · 2024Review
- An Enhancement of Outdoor Location-Based Augmented Reality Anchor Precision through VSLAM and Google Street View.Sensors (Basel, Switzerland) · 2024Article
- Analyzing the Impact of Objects in an Image on Location Estimation Accuracy in Visual Localization.Sensors (Basel, Switzerland) · 2024Article
- A review of visual SLAM for robotics: evolution, properties, and future applications.Frontiers in robotics and AI · 2024Review
- Accurate localization of indoor high similarity scenes using visual slam combined with loop closure detection algorithm.PloS one · 2024Article
- A Semantic Topology Graph to Detect Re-Localization and Loop Closure of the Visual Simultaneous Localization and Mapping System in a Dynamic Environment.Sensors (Basel, Switzerland) · 2023Article
- RBF-Based Camera Model Based on a Ray Constraint to Compensate for Refraction Error.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous Localization and Mapping (VSLAM) methods refer to the SLAM approaches that employ cameras for pose estimation and map reconstruction and are preferred over Light Detection And Ranging (LiDAR)-based methods due to their lighter weight, lower acquisition costs, and richer environment representation. Hence, several VSLAM approaches have evolved using different camera types (e.g., monocular or stereo), and have been tested on various datasets (e.g., Technische Universität München (TUM) RGB-D or European Robotics Challenge (EuRoC)) and in different conditions (i.e., indoors and outdoors), and employ multiple methodologies to have a better understanding of their surroundings. The mentioned variations have made this topic popular for researchers and have resulted in various methods. In this regard, the primary intent of this paper is to assimilate the wide range of works in VSLAM and present their recent advances, along with discussing the existing challenges and trends. This survey is worthwhile to give a big picture of the current focuses in robotics and VSLAM fields based on the concentrated resolutions and objectives of the state-of-the-art. This paper provides an in-depth literature survey of fifty impactful articles published in the VSLAMs domain. The mentioned manuscripts have been classified by different characteristics, including the novelty domain, objectives, employed algorithms, and semantic level. The paper also discusses the current trends and contemporary directions of VSLAM techniques that may help researchers investigate them.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.