Reliable localization methods for intelligent vehicles based on environment perception

Mención Internacional en el título de doctorIn the near past, we would see autonomous vehicles and Intelligent Transport Systems (ITS) as a potential future of transportation. Today, thanks to all the technological advances in recent years, the feasibility of such systems is no longer a question. Some of these autonomous driving technologies are already sharing our roads, and even commercial vehicles are including more Advanced Driver-Assistance Systems (ADAS) over the years. As a result, transportation is becoming more efficient and the roads are considerably safer. One of the fundamental pillars of an autonomous system is self-localization. An accurate and reliable estimation of the vehicle’s pose in the world is essential to navigation. Within the context of outdoor vehicles, the Global Navigation Satellite System (GNSS) is the predominant localization system. However, these systems are far from perfect, and their performance is degraded in environments with limited satellite visibility. Additionally, their dependence on the environment can make them unreliable if it were to change. Accordingly, the goal of this thesis is to exploit the perception of the environment to enhance localization systems in intelligent vehicles, with special attention to their reliability. To this end, this thesis presents several contributions: First, a study on exploiting 3D semantic information in LiDAR odometry is presented, providing interesting insights regarding the contribution to the odometry output of each type of element in the scene. The experimental results have been obtained using a public dataset and validated on a real-world platform. Second, a method to estimate the localization error using landmark detections is proposed, which is later on exploited by a landmark placement optimization algorithm. This method, which has been validated in a simulation environment, is able to determine a set of landmarks so the localization error never exceeds a predefined limit. Finally, a cooperative localization algorithm based on a Genetic Particle Filter is proposed to utilize vehicle detections in order to enhance the estimation provided by GNSS systems. Multiple experiments are carried out in different simulation environments to validate the proposed method.En un pasado no muy lejano, los vehículos autónomos y los Sistemas Inteligentes del Transporte (ITS) se veían como un futuro para el transporte con gran potencial. Hoy, gracias a todos los avances tecnológicos de los últimos años, la viabilidad de estos sistemas ha dejado de ser una incógnita. Algunas de estas tecnologías de conducción autónoma ya están compartiendo nuestras carreteras, e incluso los vehículos comerciales cada vez incluyen más Sistemas Avanzados de Asistencia a la Conducción (ADAS) con el paso de los años. Como resultado, el transporte es cada vez más eficiente y las carreteras son considerablemente más seguras. Uno de los pilares fundamentales de un sistema autónomo es la autolocalización. Una estimación precisa y fiable de la posición del vehículo en el mundo es esencial para la navegación. En el contexto de los vehículos circulando en exteriores, el Sistema Global de Navegación por Satélite (GNSS) es el sistema de localización predominante. Sin embargo, estos sistemas están lejos de ser perfectos, y su rendimiento se degrada en entornos donde la visibilidad de los satélites es limitada. Además, los cambios en el entorno pueden provocar cambios en la estimación, lo que los hace poco fiables en ciertas situaciones. Por ello, el objetivo de esta tesis es utilizar la percepción del entorno para mejorar los sistemas de localización en vehículos inteligentes, con una especial atención a la fiabilidad de estos sistemas. Para ello, esta tesis presenta varias aportaciones: En primer lugar, se presenta un estudio sobre cómo aprovechar la información semántica 3D en la odometría LiDAR, generando una base de conocimiento sobre la contribución de cada tipo de elemento del entorno a la salida de la odometría. Los resultados experimentales se han obtenido utilizando una base de datos pública y se han validado en una plataforma de conducción del mundo real. En segundo lugar, se propone un método para estimar el error de localización utilizando detecciones de puntos de referencia, que posteriormente es explotado por un algoritmo de optimización de posicionamiento de puntos de referencia. Este método, que ha sido validado en un entorno de simulación, es capaz de determinar un conjunto de puntos de referencia para el cual el error de localización nunca supere un límite previamente fijado. Por último, se propone un algoritmo de localización cooperativa basado en un Filtro Genético de Partículas para utilizar las detecciones de vehículos con el fin de mejorar la estimación proporcionada por los sistemas GNSS. El método propuesto ha sido validado mediante múltiples experimentos en diferentes entornos de simulación.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridSecretario: Joshué Manuel Pérez Rastelli.- Secretario: Jorge Villagrá Serrano.- Vocal: Enrique David Martí Muño

Study of the Effect of Exploiting 3D Semantic Segmentation in LiDAR Odometry

This article belongs to the Special Issue Intelligent Transportation SystemsThis paper presents a study of how the performance of LiDAR odometry is affected by the preprocessing of the point cloud through the use of 3D semantic segmentation. The study analyzed the estimated trajectories when the semantic information is exploited to filter the original raw data. Different filtering configurations were tested: raw (original point cloud), dynamic (dynamic obstacles are removed from the point cloud), dynamic vehicles (vehicles are removed), far (distant points are removed), ground (the points belonging to the ground are removed) and structure (only structures and objects are kept in the point cloud). The experiments were performed using the KITTI and SemanticKITTI datasets, which feature different scenarios that allowed identifying the implications and relevance of each element of the environment in LiDAR odometry algorithms. The conclusions obtained from this work are of special relevance for improving the efficiency of LiDAR odometry algorithms in all kinds of scenarios.Research was supported by the Spanish Government through the CICYT projects (TRA2016-78886-C3-1-R and RTI2018-096036-B-C21) and the Comunidad de Madrid through SEGVAUTO-4.0-CM (P2018/EMT-4362) and PEAVAUTO-CM-UC3M

An Appearance-Based Tracking Algorithm for Aerial Search and Rescue Purposes

The automation of the Wilderness Search and Rescue (WiSAR) task aims for high levels of understanding of various scenery. In addition, working in unfriendly and complex environments may cause a time delay in the operation and consequently put human lives at stake. In order to address this problem, Unmanned Aerial Vehicles (UAVs), which provide potential support to the conventional methods, are used. These vehicles are provided with reliable human detection and tracking algorithms; in order to be able to find and track the bodies of the victims in complex environments, and a robust control system to maintain safe distances from the detected bodies. In this paper, a human detection based on the color and depth data captured from onboard sensors is proposed. Moreover, the proposal of computing data association from the skeleton pose and a visual appearance measurement allows the tracking of multiple people with invariance to the scale, translation and rotation of the point of view with respect to the target objects. The system has been validated with real and simulation experiments, and the obtained results show the ability to track multiple individuals even after long-term disappearances. Furthermore, the simulations present the robustness of the implemented reactive control system as a promising tool for assisting the pilot to perform approaching maneuvers in a safe and smooth manner.This research is supported by Madrid Community project SEGVAUTO 4.0 P2018/EMT-4362) and by the Spanish Government CICYT projects (TRA2015-63708-R and TRA2016-78886-C3-1-R), and Ministerio de Educación, Cultura y Deporte para la Formación de Profesorado Universitario (FPU14/02143). Also, we gratefully acknowledge the support of the NVIDIA Corporation with the donation of the GPUs used for this research

Sirena: Autonomous integrated system for naval recognition and exploration

Peer Reviewe

Project ARES: Driverless transportation system. Challenges and approaches in an unstructured road

This article belongs to the Special Issue Intelligent Control of Mobile Robotics.The expansion of electric vehicles in urban areas has paved the way toward the era of autonomous vehicles, improving the performance in smart cities and upgrading related driving problems. This field of research opens immediate applications in the tourism areas, airports or business centres by greatly improving transport efficiency and reducing repetitive human tasks. This project shows the problems derived from autonomous driving such as vehicle localization, low coverage of 4G/5G and GPS, detection of the road and navigable zones including intersections, detection of static and dynamic obstacles, longitudinal and lateral control and cybersecurity aspects. The approaches proposed in this article are sufficient to solve the operational design of the problems related to autonomous vehicle application in the special locations such as rough environment, high slopes and unstructured terrain without traffic rules.Research is supported by the Spanish Government through the CICYT projects (PID2019-104793RB-C31 and RTI2018-096036-B-C21), the Comunidad de Madrid through SEGVAUTO-4.0-CM (P2018/EMT-4362) and through EAI of the Ministry of Science and Innovation of the Government of Spain project RTI2018-095143-B-C2

A Research Platform for Autonomous Vehicles Technologies Research in the Insurance Sector

This article belongs to the Special Issue Intelligent Transportation SystemsThis work presents a novel platform for autonomous vehicle technologies research for the insurance sector. The platform has been collaboratively developed by the insurance company MAPFRE-CESVIMAP, Universidad Carlos III de Madrid and INSIA of the Universidad Politécnica de Madrid. The high-level architecture and several autonomous vehicle technologies developed using the framework of this collaboration are introduced and described in this work. Computer vision technologies for environment perception, V2X communication capabilities, enhanced localization, human–machine interaction and self awareness are among the technologies which have been developed and tested. Some use cases that validate the technologies presented in the platform are also presented; these use cases include public demonstrations, tests of the technologies and international competitions for self-driving technologies.Research was supported by the Spanish Government through the CICYT projects (TRA2016-78886-C3-1-R and RTI2018-096036-B-C21) and the Comunidad de Madrid through SEGVAUTO-4.0-CM (P2018/EMT-4362) and PEAVAUTO-CM-UC3M

Sirena: Autonomous integrated system for naval recognition and exploration

Peer Reviewe

A multi-taxa assessment of aquatic non-indigenous species introduced into Iberian freshwater and transitional waters

Aquatic ecosystems are particularly vulnerable to the introduction of non-indigenous species (NIS), leading to multi-faceted ecological, economic and health impacts worldwide. The Iberian Peninsula comprises an exceptionally biodiverse Mediterranean region with a high number of threatened and endemic aquatic species, most of them strongly impacted by biological invasions. Following a structured approach that combines a systematic review of available information and expert opinion, we provide a comprehensive and updated multi-taxa inventory of aquatic NIS (fungi, macroalgae, vascular plants, invertebrates and vertebrates) in Iberian inland waters. Moreover, we assess overall patterns in the establishment status, introduction pathways, native range and temporal introduction trends of listed NIS. In addition, we discuss the legal coverage provided by both national (Spanish and Portuguese) and European NIS regulations. We inventoried 326 aquatic NIS in Iberian inland waters, including 215 established, 96 with uncertain establishment status and 15 cryptogenic taxa. Invertebrates (54.6%) and vertebrates (24.5%) were the groups with the highest number of NIS, with Arthropoda, Mollusca, and Chordata being the most represented phyla. Recorded NIS originated from diverse geographic regions, with North and South America being the most frequent. Vertebrates and vascular plants were mostly introduced through intentional pathways (i.e. release and escape), whereas invertebrates and macroalgae arrived mostly through unintentional ways (i.e. contaminant or stowaway). Most of the recorded NIS were introduced in Iberian inland waters over the second half of the 20th century, with a high number of NIS introductions being reported in the 2000s. While only 8% of the recorded NIS appear in the European Union list of Invasive Alien Species of Union concern, around 25% are listed in the Spanish and Portuguese NIS regulations. This study provides the most updated checklist of Iberian aquatic NIS, meeting the requirements set by the EU regulation and providing a baseline for the evaluation of its application. We point out the need for coordinated transnational strategies to properly tackle aquatic invasions across borders of the EU members

Lista de especies exóticas acuáticas de la Península Ibérica (2020)

Se presenta una lista actualizada de las especies exóticas que se encuentran en etapa de establecimiento o de propagación de la invasión en aguas continentales de la península ibérica. La lista está basada en la evaluación sistemática de los datos en colaboración con un amplio equipo de expertos de España y Portugal. Esta lista de actualización es un instrumento de apoyo importante para la aplicación del Reglamento de la Unión Europea (UE) sobre las especies exóticas invasoras (EEI) y también proporciona una base objetiva para el examen de su aplicación. En última instancia, la información incluida puede utilizarse para supervisar el cumplimiento del objetivo de la Estrategia de la UE sobre diversidad biológica hasta 2030 para combatir las EEI, pero también para la aplicación de otras políticas de la UE con requisitos sobre especies exóticas, como las Directivas de Hábitats y Aves, la Directiva Marco sobre la Estrategia Marina (DMEM) y la Directiva Marco del Agua (DMA)

Lista de especies exóticas acuáticas de la Península Ibérica (2020)

Se presenta una lista actualizada de las especies exóticas que se encuentran en etapa de establecimiento o de propagación de la invasión en aguas continentales de la península ibérica. La lista está basada en la evaluación sistemática de los datos en colaboración con un amplio equipo de expertos de España y Portugal. Esta lista de actualización es un instrumento de apoyo importante para la aplicación del Reglamento de la Unión Europea (UE) sobre las especies exóticas invasoras (EEI) y también proporciona una base objetiva para el examen de su aplicación. En última instancia, la información incluida puede utilizarse para supervisar el cumplimiento del objetivo de la Estrategia de la UE sobre diversidad biológica hasta 2030 para combatir las EEI, pero también para la aplicación de otras políticas de la UE con requisitos sobre especies exóticas, como las Directivas de Hábitats y Aves, la Directiva Marco sobre la Estrategia Marina (DMEM) y la Directiva Marco del Agua (DMA)