A survey of state-of-the-art on visual SLAM
Iman Abaspur Kazerouni, Luke Fitzgerald, Gerard Dooly, Daniel Toal
Abstract
This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We discuss the basic definitions in the SLAM and vision system fields and provide a review of the state-of-the-art methods utilized for mobile robot’s vision and SLAM. This paper covers topics from the basic SLAM methods, vision sensors, machine vision algorithms for feature extraction and matching, Deep Learning (DL) methods and datasets for Visual Odometry (VO) and Loop Closure (LC) in V-SLAM applications. Several feature extraction and matching algorithms are simulated to show a better vision of feature-based techniques.
Topics & Concepts
Simultaneous localization and mappingArtificial intelligenceComputer scienceComputer visionMatching (statistics)Feature (linguistics)Visual odometryFeature extractionOdometryFeature matchingMobile robotRobot visionRobotMathematicsStatisticsPhilosophyLinguisticsRobotics and Sensor-Based LocalizationAdvanced Image and Video Retrieval TechniquesRobotic Path Planning Algorithms