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An RGB-D based Augmented Reality 3D Reconstruction System for Robotic Environmental Inspection of Radioactive Areas

Topics: Engineering Applications; Guidance, Navigation and Control; Human-Robots Interfaces; Mobile Robots and Autonomous Systems; Perception and Awareness; Robot Design, Development and Control; Sensors Fusion; Surveillance, Fault Detection and Diagnosis; Telerobotics and Teleoperation; Virtual Environment, Virtual and Augmented Reality; Vision, Recognition and Reconstruction

Authors: Giacomo Lunghi 1 ; Raul Marin Prades 2 ; Mario Di Castro 3 ; Manuel Ferre 4 and Alessandro Masi 5

Affiliations: 1 CERN and Universitat Jaume I, Switzerland ; 2 Universitat Jaume I, Spain ; 3 CERN and Centre for Automation and Robotics UPM-CSIC, Switzerland ; 4 Centre for Automation and Robotics UPM-CSIC, Spain ; 5 CERN, Switzerland

Keyword(s): Robotic Systems, 3D Reconstruction, Sensors Fusion, Environmental Monitoring and Control, Guidance, Navigation and Control, 3D Reconstruction and Augmented Reality.

Related Ontology Subjects/Areas/Topics: Engineering Applications ; Human-Robots Interfaces ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Mobile Robots and Autonomous Systems ; Perception and Awareness ; Robot Design, Development and Control ; Robotics and Automation ; Sensors Fusion ; Signal Processing, Sensors, Systems Modeling and Control ; Surveillance ; Telerobotics and Teleoperation ; Virtual Environment, Virtual and Augmented Reality ; Vision, Recognition and Reconstruction

Abstract: Preparing human intervention in hazardous, unknown and unstructured environments is a difficult task. The intervention should focus on the optimization of the operations in order to reduce the personnel exposure to hazards. Optimizing these operations is not always possible, due to a lack of information about the intervention environment: such information can be collected through a robotic inspection before the preparation of the intervention. The data collected during this inspection, such as radiation, temperature and oxygen level, must be accurate and precisely positioned in the environment in order to optimize the humans approaching path and their stay in the intervention area. In this paper we present a robotic system for collecting physical quantities, precisely positioned in the environment, which is easy to use by the robot operator and it is seamlessly integrated in the robot control. The operator is helped by the system in finding the most dangerous zones, which collects al l the sensor readings while building a 3D model of the environment. Preliminary results are presented using CERN's accelerators facilities as testing area. (More)

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Paper citation in several formats:
Lunghi, G.; Marin Prades, R.; Di Castro, M.; Ferre, M. and Masi, A. (2017). An RGB-D based Augmented Reality 3D Reconstruction System for Robotic Environmental Inspection of Radioactive Areas. In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-264-6; ISSN 2184-2809, SciTePress, pages 233-238. DOI: 10.5220/0006395802330238

@conference{icinco17,
author={Giacomo Lunghi. and Raul {Marin Prades}. and Mario {Di Castro}. and Manuel Ferre. and Alessandro Masi.},
title={An RGB-D based Augmented Reality 3D Reconstruction System for Robotic Environmental Inspection of Radioactive Areas},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2017},
pages={233-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006395802330238},
isbn={978-989-758-264-6},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - An RGB-D based Augmented Reality 3D Reconstruction System for Robotic Environmental Inspection of Radioactive Areas
SN - 978-989-758-264-6
IS - 2184-2809
AU - Lunghi, G.
AU - Marin Prades, R.
AU - Di Castro, M.
AU - Ferre, M.
AU - Masi, A.
PY - 2017
SP - 233
EP - 238
DO - 10.5220/0006395802330238
PB - SciTePress