Projecte llegit
Títol: DEVELOPMENT OF A PAYLOAD FOR INDOOR MAPPING AND EXTENDED USES
Director/a: HORNERO OCAÑA, GEMMA
Departament: EEL
Títol: DEVELOPMENT OF A PAYLOAD FOR INDOOR MAPPING AND EXTENDED USES
Data inici oferta: 30-01-2019 Data finalització oferta: 30-09-2019
Estudis d'assignació del projecte:
MU DRONS
| Tipus: Individual | |
| Lloc de realització: Fora UPC | |
| Supervisor/a extern: EULÀLIA PARÉS | |
| Institució/Empresa: CTTC | |
| Titulació del Director/a: Msc Mathematics | |
| Paraules clau: | |
| photogrammetry, drone, UAV, RPAS, UAS, georeferencing, GIS, mapping | |
| Descripció del contingut i pla d'activitats: | |
| We envisage using a small RPAS to generate 3D models of the
interior of buildings affected by the disaster using camera images or laser scanners. The main goal of the project is to provide an understandable representation of a building affected by some kind of disaster, enough to help rescue teams in their task. In order to achieve that goal is necessary to: • Properly understand the use case and the user requirements • Select a suitable platform and design an appropriate payload for the user • Define the procedure for system deployment and data acquisition campaign • Select an appropriate GIS system for information visualization • Study additional/extended uses of the indoor cartography already generated • And last but not least, carry on a successful validation campaign |
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| Overview (resum en anglès): | |
| The project aims to develop a low-cost system, which can serve as a payload on a small RPAS for data acquisition while performing online near real-time mapping mission based on visual-inertial Simultaneous Localization and Mapping (SLAM) in a post-disaster indoor scenario. The project mainly includes four phases. First, the use case for disaster management and the corresponding user requirements have been defined. Secondly, the hardware and software architecture has been designed based on the system requirements after the feasibility study. The payload prototype consists of an Odroid XU4 single board computer, GNSS/IMU module, and an Intelrealsense D435 RGB-D camera. Thirdly, the detail data-processing approaches have been implemented and tested. The onboard platform runs on UBUNTU 16.04. ROS. Extend Kalman Filter (EKF) is used for data fusion of the IMU and visual odometry generated from the RGB-D camera. Back-end from the RTABMAP ros package is used for loop detection and detect loop and minimize global inconsistencies of the map based on pose graph optimization methods. Post-processing procedures have been proposed to refine the mapping results and generate 2D floorplans. Finally, verification and validation work has been done in several indoor scenarios to evaluate the performance of the system. The onboard system has been able to map an indoor office room and a challenging floor. Due to hardware and time limitation, planned flight tests were not able to be carried out and have been left for future work.
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