Sky-GVINS: a Sky-segmentation Aided GNSS-Visual-Inertial System for Robust Navigation in Urban Canyons

Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous Localization and Mapping (SLAM) systems draws increasing attention to a global and continuous localization solution. Nonetheless, in dense urban environments, GNSS-based SLAM systems will suffer from the Non-Line-Of-Sight (NLOS) measurements, which might lead to a sharp deterioration in localization results. In this paper, we propose to detect the sky area from the up-looking camera to improve GNSS measurement reliability for more accurate position estimation. We present Sky-GVINS: a sky-aware GNSS-Visual-Inertial system based on a recent work called GVINS. Specifically, we adopt a global threshold method to segment the sky regions and non-sky regions in the fish-eye sky-pointing image and then project satellites to the image using the geometric relationship between satellites and the camera. After that, we reject satellites in non-sky regions to eliminate NLOS signals. We investigated various segmentation algorithms for sky detection and found that the Otsu algorithm reported the highest classification rate and computational efficiency, despite the algorithm's simplicity and ease of implementation. To evaluate the effectiveness of Sky-GVINS, we built a ground robot and conducted extensive real-world experiments on campus. Experimental results show that our method improves localization accuracy in both open areas and dense urban environments compared to the baseline method. Finally, we also conduct a detailed analysis and point out possible further directions for future research. For detailed information, visit our project website at https://github.com/SJTU-ViSYS/Sky-GVINS

Improving Navigation in GNSS-challenging Environments: Multi-UAS Cooperation and Generalized Dilution of Precision

This paper presents an approach to tackle navigation challenges for Unmanned Aircraft Systems flying under non nominal GNSS coverage. The concept used to improve navigation performance in these environments consists in using one or more cooperative platforms and relative sensing measurements (based on vision and/or ranging) to the navigation aid. The paper details the cooperative navigation filter which can exploit multiple cooperative platforms and multiple relative measurements, while also using partial GNSS information. The achievable navigation accuracy can be predicted using the concept of "generalized dilution of precision", which derives from applying the idea of dilution of precision to the mathematical structure of the cooperative navigation filter. Values and trends of generalized dilution of precision are discussed as a function of the relative geometry in common GNSS-challenging scenarios. Finally, navigation performance is assessed based on simulations and on multi-drone flight tests

A New Cooperative PPP-RTK System with Enhanced Reliability in Challenging Environments

Compared to the traditional PPP-RTK methods, cooperative PPP-RTK methods provide expandable service coverage and eliminate the need for a conventional expensive data processing center and the establishment and maintenance of a permanently deployed network of dense GNSS reference stations. However, current cooperative PPP-RTK methods suffer from some major limitations. First, they require a long initialization period before the augmentation service can be made available from the reference stations, which decreases their usability in practical applications. Second, the inter-reference station baseline ambiguity resolution (AR) and regional atmospheric model, as presented in current state-of-art PPP-RTK and network RTK (NRTK) methods, are not utilized to improve the accuracy and service coverage of the network augmentation. Third, the positioning performance of current PPP-RTK methods would be significantly degraded in challenging environments due to multipath effects, non-line-of-sight (NLOS) errors, poor satellite visibility and geometry caused by severe signal blockages. Finally, current position domain or ambiguity domain partial ambiguity resolution (PAR) methods suffer from high false alarm and miss detection, particularly in challenging environments with poor satellite geometry and observations contaminated by NLOS effect, gross errors, biases, and high observation noise. This thesis proposed a new cooperative PPP-RTK positioning system, which offers significant improvements to provide fast-initialization, scalable coverage, and decentralized real-time kinematic precise positioning with enhanced reliability in challenging environments. The system is composed of three major components. The first component is a new cooperative PPP-RTK framework in which a scalable chain of cooperative static or moving reference stations, generates single reference station-derived or reference station network-derived state-space-representation (SSR) corrections for fast ambiguity resolution at surrounding user stations with no need for a conventional expensive data processing center. The second component is a new multi-feature support vector machine (SVM) signal classifier based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. The third component is a new PAR method based on machine learning, which employs the combination of two support vector machine (SVM) to effectively identify and exclude bias sources from PAR without relying on satellite geometry. The prototype of the new PPP-RTK system is developed and substantially tested using publically available real-time SSR products from International GNSS Service (IGS) Real-Time Service (RTS)

Arquitectura software y de navegación para vehículo autónomo

La importancia de los vehículos autónomos en el sector del transporte durante las próximas décadas es ya un hecho. La implementación a gran escala de estos vehículos supondrá una serie de ventajas entre las que destacan una conducción más segura y por lo tanto una disminución de los accidentes de tráfico, una reducción de las emisiones y del consumo energético y un acortamiento de los tiempos de trayecto. Sin embargo, existen todavía numerosos problemas por resolver de cara a una conducción completamente autónoma y generalizada. Todavía es necesario investigar en distintas tecnologías como percepción, control o navegación. Esta última área, es especialmente crítica ya que el correcto movimiento del vehículo depende de una localización y planificación de trayectorias robustas y fiables, entre otras tareas de navegación. Además, también es necesario estudiar la relación y el funcionamiento conjunto de todos los módulos de estas áreas junto con el hardware y entre ellas, relaciones definidas por la arquitectura. El objetivo de esta tesis es: Por una parte, desarrollar una plataforma de investigación constituida por un vehículo autónomo completamente funcional, en la que se puedan probar distintos algoritmos relacionados con la conducción autónoma. Se investigarán las distintas arquitecturas posibles y se describirá la incorporada al vehículo desarrollado. Por otra parte, esta tesis presenta los avances realizados en el área de la navegación para mejorar la localización del vehículo en entornos mixtos donde métodos convencionales basados en GNSS o la correlación entre un mapa y las lecturas del LiDAR no obtienen resultados precisos, así como los avances en predicción del movimiento de otros vehículos, necesarios para una buena planificación de trayectorias. Además se investigará acerca de la interacción entre peatones y vehículos autónomos, y cómo mejorarla haciendo uso de distintas interfaces de comunicación. Los resultados de los algoritmos desarrollados en localización y predicción de trayectorias han sido obtenidos con bases de datos públicas y comparados con métodos del estado del arte a los que superan en precisión, mientras que los resultados relativos a la interacción entre peatones y vehículos autónomos se ha evaluado mediante experimentos reales. Además, la arquitectura completa del vehículo ha sido probada en distintos experimentos que certifican su correcto funcionamiento.The importance of autonomous vehicles in the transportation sector over the next decades is already a fact. The large-scale implementation of these vehicles will bring several advantages, including safer driving and therefore a decrease of traffic fatalities, lower emissions and energy consumption, and shorter journey times. However, there are still many issues to be solved for fully autonomous and widespread driving. A deeper research is still needed in different technologies such as perception, control and navigation. This last area is especially critical since the correct movement of the vehicle depends on precise localization and a robust and reliable path planning, among other navigation tasks. In addition, it is also necessary to study the relationships and the joint operation of all the modules of these areas together with the hardware and between them, relationships defined by the architecture. The objective of this thesis is: On the one hand, to develop a research platform consisting of a fully functional autonomous vehicle, on which different algorithms related to autonomous driving can be tested. The different possible architectures will be investigated and the one incorporated in the developed vehicle will be described. On the other hand, this thesis presents the advances made in the area of navigation to improve vehicle localization in mixed environments where conventional methods based on GNSS or the correlation between a map and LiDAR readings do not obtain accurate results, as well as advances in predicting the movement of other vehicles, necessary for good trajectory planning. In addition, the interaction between pedestrians and autonomous vehicles will be studied, and how to improve it using different communication interfaces. The results of the developed algorithms in localization and trajectory prediction have been obtained with public databases and compared with state-of-the-art methods which are outperformed in termos of accuracy, while the results related to the interaction between pedestrians and autonomous vehicles have been evaluated by means of real experiments. In addition, the complete vehicle architecture has been tested in different experiments certifying its correct operation.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Ignacio Parra Alonso.- Secretario: Carlos Guindel Gómez.- Vocal: Noelia Hernández Parr