Abstract
Abstract. In this work we present the development of a prototype, mobile mapping platform with modular design and architecture that can be suitably modified to address effectively both outdoors and indoors environments. Our system is built on the Robotics Operation System (ROS) and utilizes multiple sensors to capture images, pointclouds and 3D motion trajectories. These include synchronized cameras with wide angle lenses, a lidar sensor, a GPS/IMU unit and a tracking optical sensor. We report on the individual components of the platform, it’s architecture, the integration and the calibration of its components, the fusion of all recorded data and provide initial 3D reconstruction results. The processing algorithms are based on existing implementations of SLAM (Simultaneous Localisation and Mapping) methods combined with SfM (Structure-from-Motion) for optimal estimations of orientations and 3D pointclouds. The scope of this work, which is part of an ongoing H2020 program, is to digitize the physical world, collect relevant spatial data and make digital copies available to experts and public for covering a wide range of needs; remote access and viewing, process, design, use in VR etc.
Highlights
Urban planning and public infrastructure management are application areas that benefit from such technologies as they require constantly updated geographic information
After a short review of related work, we present the individual sensors and components of our platform, we describe their integration within the Robotics Operation System (ROS) and discuss processing workflows for generating 3D reconstructions from the collected data
CONCLUDING REMARKS In this contribution we presented a first implementation of a modular mobile mapping platform that is based on commercial hardware components and open source software libraries
Summary
Urban planning and public infrastructure management are application areas that benefit from such technologies as they require constantly updated geographic information. Mobile mapping technologies have been widely used in a variety of applications in urban areas, for mapping transportation infrastructure, utilities, buildings, vegetation and lately for autonomous vehicle driving (Shi et al, 2017). The scope of our research is to provide a tool that captures multiple types of relevant spatial data of the environment such as raw video footage, georeferenced imagery, pointclouds etc. These can be subsequently exploited by designers and artists to collaborate with scientists and engineers towards the creation of innovative designs and experiences.
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