A Model-Free Approach for Accurate Joint Motion Control in Humanoid Locomotion

A new model-free approach to precisely control humanoid robot joints is presented in this article. An input&-output online identification procedure will permit to compensate neglected or uncertain dynamics, such as, on the one hand, transmission and compliance nonlinear effects, and, on the other hand, network transmission delays. Robustness toparameter variations will be analyzed and compared to other advanced PID-based controllers. Simulations will show that not only good tracking quality can be obtained with this novel technique, but also that it provides a very robust behavior to the closed-loop system. Furthermore, a locomotion task will be tested in a complete humanoid simulatorto highlight the suitability of this control approach for such complex systems.This work has been supported by the CAM Project S2009/DPI-1559/ROBOCITY2030 II, developed by the research team RoboticsLab at the University Carlos III of Madrid.Publicad

Localization Method for Autonomous Vehicles by using Vertical Elements in the Environment

The goal of this work is to provide autonomous cars with an alternative method to estimate their position in the world. It focuses on those situations when the GPS signal gets imprecise, weak or even lost due to environment conditions (long tunnels, dense forests, high buildings around, etc.). By installing two Velodyne VLP-16 LiDAR devices on the top of the car, located on both front corners of the vehicle structure, it is possible to acquire a 3D representation of this environment as a point cloud. This point cloud will be analyzed in order to find thin, vertical elements, such as traffic signals, traffic lights and so on. If these elements have been previously georeferenced, this is, their coordinates have been acquired and saved, the method will try to compare and match the incoming information from the environment to the georeferenced objects, i.e., performing data association. If the detected elements match any of the georeferenced ones, the car will correct an estimate of its position in a global frame.RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, funded by R&D Activities Program in Comunidad de Madrid and cofunded by EU Structural Funds.Peer reviewe

Experimental Application of Hybrid Fractional-Order Adaptive Cruise Control at Low Speed

International audienceThis brief deals with the design and experimen-tal application of a hybrid fractional adaptive cruise control (ACC) at low speeds. First, an improved fractional-order cruise control (CC) is presented for a commercial Citroën C3 prototype—which has automatic driving capabilities—at low speeds, which considers a hybrid model of the vehicle. The quadratic stability of the system is proved using a frequency domain method. Second, ACC maneuvers are implemented with two different distance policies using two cooperating vehicles— one manual, the leader, and the other, automatic—also at very low speeds. In these maneuvers, the objective is to maintain a desired interdistance between the leader and follower vehi-cles, i.e., to perform a distance control—with a proportional differential (PD) controller in this case—in which the previously designed fractional-order CC is used for the speed control. Simulation and experimental results, obtained in a real circuit, are given to demonstrate the effectiveness of the proposed control strategies. Index Terms— Adaptive cruise control (ACC), fractional-order control (FOC), hybrid system and control, stability

Sistema de cifrado basado en contexto aplicado a prevención de fuga de datos

[ES] Las herramientas DLP (Data Leak Prevention) están adquiriendo un valor elevado en los últimos años debido a la importancia de proteger los datos sensibles de una organización. Muchas de las herramientas DLP se basan principalmente en la analítica de datos, ya sea un análisis de archivos almacenados o estando en tránsito por la red. La solución DLP propuesta usa el cifrado basado en contexto para evitar fugas de información. La clave de cifrado y descifrado se obtiene a partir de la ejecución de un conjunto de retos basados en el contexto de entorno y en las políticas de la empresa. En este artículo se explica la arquitectura y el diseño de la solución DLP y de los retos propuestos.Este trabajo ha sido parcialmente financiado con el apoyo del MINECO (proyecto DroneFS), con el código RTC-2015-4064-8 y del MINETUR (proyecto CiberNoid) con el código TSI-100200-2015-035.Garcia, A.; Holgado, P.; Garcia, J.; Roncero, J.; Villagrá, V.; Jalain, H. (2018). Sistema de cifrado basado en contexto aplicado a prevención de fuga de datos. En XIII Jornadas de Ingeniería telemática (JITEL 2017). Libro de actas. Editorial Universitat Politècnica de València. 93-100. https://doi.org/10.4995/JITEL2017.2017.6576OCS9310

Traffic jam driving with NMV avoidance

n recent years, the development of advanced driver assistance systems (ADAS) – mainly based on lidar and cameras – has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations—in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuators – brake and throttle pedals – were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging

A Comparison of FPGA and GPGPU Designs for Bayesian Occupancy Filters

Grid-based perception techniques in the automotive sector based on fusing information from different sensors and their robust perceptions of the environment are proliferating in the industry. However, one of the main drawbacks of these techniques is the traditionally prohibitive, high computing performance that is required for embedded automotive systems. In this work, the capabilities of new computing architectures that embed these algorithms are assessed in a real car. The paper compares two ad hoc optimized designs of the Bayesian Occupancy Filter; one for General Purpose Graphics Processing Unit (GPGPU) and the other for Field-Programmable Gate Array (FPGA). The resulting implementations are compared in terms of development effort, accuracy and performance, using datasets from a realistic simulator and from a real automated vehicle.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness with the National Projects TCAP-AUTO (RTC-2015-3942-4) and NAVEGASE (DPI2014-53525-C3-1-R)

A Review of the Bayesian Occupancy Filter

Autonomous vehicle systems are currently the object of intense research within scientific and industrial communities; however, many problems remain to be solved. One of the most critical aspects addressed in both autonomous driving and robotics is environment perception, since it consists of the ability to understand the surroundings of the vehicle to estimate risks and make decisions on future movements. In recent years, the Bayesian Occupancy Filter (BOF) method has been developed to evaluate occupancy by tessellation of the environment. A review of the BOF and its variants is presented in this paper. Moreover, we propose a detailed taxonomy where the BOF is decomposed into five progressive layers, from the level closest to the sensor to the highest abstract level of risk assessment. In addition, we present a study of implemented use cases to provide a practical understanding on the main uses of the BOF and its taxonomy.This work has been founded by the Spanish Ministry of Economy and Competitiveness along with the European Structural and Investment Funds in the National Project TCAP-AUTO (RTC-2015-3942-4) in the program of “Retos Colaboración 2014”

White Paper 11: Artificial intelligence, robotics & data science

198 p. : 17 cmSIC white paper on Artificial Intelligence, Robotics and Data Science sketches a preliminary roadmap for addressing current R&D challenges associated with automated and autonomous machines. More than 50 research challenges investigated all over Spain by more than 150 experts within CSIC are presented in eight chapters. Chapter One introduces key concepts and tackles the issue of the integration of knowledge (representation), reasoning and learning in the design of artificial entities. Chapter Two analyses challenges associated with the development of theories –and supporting technologies– for modelling the behaviour of autonomous agents. Specifically, it pays attention to the interplay between elements at micro level (individual autonomous agent interactions) with the macro world (the properties we seek in large and complex societies). While Chapter Three discusses the variety of data science applications currently used in all fields of science, paying particular attention to Machine Learning (ML) techniques, Chapter Four presents current development in various areas of robotics. Chapter Five explores the challenges associated with computational cognitive models. Chapter Six pays attention to the ethical, legal, economic and social challenges coming alongside the development of smart systems. Chapter Seven engages with the problem of the environmental sustainability of deploying intelligent systems at large scale. Finally, Chapter Eight deals with the complexity of ensuring the security, safety, resilience and privacy-protection of smart systems against cyber threats.18 EXECUTIVE SUMMARY ARTIFICIAL INTELLIGENCE, ROBOTICS AND DATA SCIENCE Topic Coordinators Sara Degli Esposti ( IPP-CCHS, CSIC ) and Carles Sierra ( IIIA, CSIC ) 18 CHALLENGE 1 INTEGRATING KNOWLEDGE, REASONING AND LEARNING Challenge Coordinators Felip Manyà ( IIIA, CSIC ) and Adrià Colomé ( IRI, CSIC – UPC ) 38 CHALLENGE 2 MULTIAGENT SYSTEMS Challenge Coordinators N. Osman ( IIIA, CSIC ) and D. López ( IFS, CSIC ) 54 CHALLENGE 3 MACHINE LEARNING AND DATA SCIENCE Challenge Coordinators J. J. Ramasco Sukia ( IFISC ) and L. Lloret Iglesias ( IFCA, CSIC ) 80 CHALLENGE 4 INTELLIGENT ROBOTICS Topic Coordinators G. Alenyà ( IRI, CSIC – UPC ) and J. Villagra ( CAR, CSIC ) 100 CHALLENGE 5 COMPUTATIONAL COGNITIVE MODELS Challenge Coordinators M. D. del Castillo ( CAR, CSIC) and M. Schorlemmer ( IIIA, CSIC ) 120 CHALLENGE 6 ETHICAL, LEGAL, ECONOMIC, AND SOCIAL IMPLICATIONS Challenge Coordinators P. Noriega ( IIIA, CSIC ) and T. Ausín ( IFS, CSIC ) 142 CHALLENGE 7 LOW-POWER SUSTAINABLE HARDWARE FOR AI Challenge Coordinators T. Serrano ( IMSE-CNM, CSIC – US ) and A. Oyanguren ( IFIC, CSIC - UV ) 160 CHALLENGE 8 SMART CYBERSECURITY Challenge Coordinators D. Arroyo Guardeño ( ITEFI, CSIC ) and P. Brox Jiménez ( IMSE-CNM, CSIC – US )Peer reviewe

Self-Generated OSM-Based Driving Corridors

Finding the boundaries of the drivable space is a key to the development of any advanced driver assistance systems with automated driving functions. A common approach found in the literature is to combine the information of digital maps with multiple on-board sensors for building a robust and accurate model of the environment from which to extract the navigable space. In this sense, the digital map is the crucial component for relating the location of the vehicle and identifying the different road features. This paper presents an automatic procedure for generating driving corridors from OpenStreetMap. The proposed method expands the original map representation, replacing polylines by polynomial-based roads, whose sections are defined using cubic Bézier curves. All curves are automatically adjusted from the original road description, thus generating an efficient and accurate road representation without human intervention. Finally, the driving corridors are generated as a concatenation of the modified road sections along a planned route. The proposed approach has been validated in a peri-urban environment, for which corridors where successfully generated in all cases.This work was supported in part by the Spanish Ministry of Economy, Industry and Competitiveness with National Project TCAP-AUTO under Grant RTC-2015-3942-4, in part by the Spanish Ministry of Science, Innovation and Universities with National Project COGDRIVE under Grant DPI2017-86915-C3-1-R, and in part by the European Commission through the Project PRYSTINE under Grant ECSEL-783190-2. The work of J. Godoy was supported by the Juan de la Cierva Fellowship Program through the Spanish Ministry of Economy, Industry and Competitiveness.Peer reviewe

Real-Time Motion Planning Approach for Automated Driving in Urban Environments

Autonomous vehicles must be able to react in a timely manner to typical and unpredictable situations in urban scenarios. In this connection, motion planning algorithms play a key role as they are responsible of ensuring driving safety and comfort while producing human-like trajectories in a wide range of driving scenarios. Typical approaches for motion planning focus on trajectory optimization by applying computation-intensive algorithms, rather than finding a balance between optimatily and computing time. However, for on-road automated driving at medium and high speeds, determinism is necessary at high sampling rates. This work presents a trajectory planning algorithm that is able to provide safe, human-like and comfortable trajectories by using cost-effective primitives evaluation based on quintic Bézier curves. The proposed method is able to consider the kinodynamic constrains of the vehicle while reactively handling dynamic real environments in real-time. The proposed motion planning strategy has been implemented in a real experimental platform and validated in different real operating environments, successfully overcoming typical urban traffic scenes where both static and dynamic objects are involved.This work was supported in part by the Spanish Ministry of Science, Innovation and Universities with National Project COGDRIVE under Grant DPI2017-86915-C3-1-R, in part by the European Commission through the Projects PRYSTINE under Grant ECSEL-783190-2, in part by SECREDAS under Grant ECSEL-783119-2, and in part by the Community of Madrid through SEGVAUTO 4.0-CM Programme under Grant S2018-EMT-4362.Peer reviewe