Abstract
Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System), also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.
Highlights
We present an ARM-based, low-cost portable prototype of a Mobile mapping systems (MMSs) based on stereo environments are often characterized by challenging illumination conditions that require vision that exploits Visual Simultaneous Localization and Mapping (V-SLAM) to keep both robust auto exposure algorithms [26,27] and careful acquisitions to avoid motion blur
V-SLAM algorithms have witnessed a growing popularity in recent years and nowadays are being used in different cutting-edge fields ranging from autonomous navigation, autonomous driving and virtual and augmented reality, to cite a few
The first two units are aimed at helping the operator to acquire an ideal imaging The realized guidance system is divided in four units: configuration according to photogrammetric principles, respecting a planned
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Ultra-Wide Band (UWB) [25] in indoor, acoustic systems in underwater environments) are expensive and/or generally require a time-consuming system set up and calibration These environments are often characterized by challenging illumination conditions that require both robust auto exposure algorithms [26,27] and careful acquisitions to avoid motion blur. We present an ARM-based, low-cost portable prototype of a MMS based on stereo environments are often characterized by challenging illumination conditions that require vision that exploits Visual Simultaneous Localization and Mapping (V-SLAM) to keep both robust auto exposure algorithms [26,27] and careful acquisitions to avoid motion blur.
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