Real-time Navigation and Mapping with Mobile Mapping Systems using LiDAR/Camera/INS/GNSS Advanced Hybridization Algorithms: Description and Test Results

A. Fernández, M. Wis, G. Vecchione, P.F. Silva, I. Colomina, Eduard Angelats, M.E. Parès

Abstract:	Modern mobile mapping systems (MMS) include one or several laser scanners and cameras complementing the core INS/GNSS navigation system. The idea of using the information available from the image and laser systems as additional source for navigation has been studied for some time. Hybridization of INSS/GNSS with LiDAR and imaging sensors, in combination with advanced signal processing in the receiver architecture, improves drastically the availability and reliability in urban environments. When GNSS fails, the navigation uses the LiDAR observations to keep controlled the inertial sensor errors. A conceptual receiver based on this approach was developed in the frame of ATENEA project [1], [2], in which a deep integration GNSS/INSS/LiDAR was prototyped in a SW receiver [3], including LiDAR-obtained planes as constraint for navigation. A comprehensive test campaign with simulated (GPS L1, Galileo E1 and Galileo E5-AltBOC) and real (GPS L1) GNSS data was carried out. A real INS and LiDAR data acquisition van test was also performed in order to assure the concept feasibility. ATENEA results showed that hybridization with LiDAR data adds more reliability to the navigation solution when the GNSS signal was contaminated with interferences or multipath in urban scenarios or simply when the satellites were shadowed by scenario buildings. After having proved the concept, DEIMOS Space (DMS) and the former Institute of Geomatics (IG, currently integrated within the CTTC) have extended the research and development activity in the frame of the so-called ATENEA+ concept. One of the aims of this research is to adapt the processing chain of the raw data to a real-time architecture receiver. This would allow the implementation of the system on a hardware prototype based on DEIMOS advanced GNSS receiver [4] and [5]. In addition, the processing algorithms have been refined and adapted in order to allow the processing of imaging cameras and odometers, and to identify and use for navigation additional features from the 3D point clouds such as lines. The camera and odometer provide more robustness and additional information that can be used to make the navigation solution more reliable. This paper presents the conceptual architecture for a real-time receiver navigation system that uses GPS/Galileo signals, INS measurements, LIDAR features, optical cameras images, and odometer observables. The feature extraction strategy from LiDAR and image data is presented, as well as the approach to combine them with GNSS and inertial data within the navigation SW. This paper also describes the processing algorithms and presents the test results obtained with simulated and real datasets demonstrating the increased accuracy and reliability. Finally, the lines of an implementation plan in a real receiver based on FPGA (as the GRIP receiver developed by DEIMOS [4]) are described.
Published in:	Proceedings of the 27th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2014) September 8 - 12, 2014 Tampa Convention Center Tampa, Florida
Pages:	896 - 904
Cite this article:	Fernández, A., Wis, M., Vecchione, G., Silva, P.F., Colomina, I., Angelats, Eduard, Parès, M.E., "Real-time Navigation and Mapping with Mobile Mapping Systems using LiDAR/Camera/INS/GNSS Advanced Hybridization Algorithms: Description and Test Results," Proceedings of the 27th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2014), Tampa, Florida, September 2014, pp. 896-904.
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