Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles

In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing data. Our results show that this asynchronous multi-sensor (GPS+IMU+CAN-based odometry) fusion is advantageous in low-speed manoeuvres, improving accuracy and robustness to missing data, thanks to non-causal filtering. The proposed algorithm is based on Extended Kalman Filter and Smoother, with exponential discretization of continuous-time stochastic differential equations, in order to process measurements at arbitrary time instants; it can provide data to subsequent processing steps at arbitrary time instants, not necessarily coincident with the original measurement ones. Given the extra information available in the smoothing case, its estimation performance is less sensitive to the noise-variance parameter setting, compared to causal filtering. Working Matlab code is provided at the end of this work

Drive Force and Longitudinal Dynamics Estimation in Heavy-Duty Vehicles

Modelling the dynamic behaviour of heavy vehicles, such as buses or trucks, can be very useful for driving simulation and training, autonomous driving, crash analysis, etc. However, dynamic modelling of a vehicle is a difficult task because there are many subsystems and signals that affect its behaviour. In addition, it might be hard to combine data because available signals come at different rates, or even some samples might be missed due to disturbances or communication issues. In this paper, we propose a non-invasive data acquisition hardware/software setup to carry out several experiments with an urban bus, in order to collect data from one of the internal communication networks and other embedded systems. Subsequently, non-conventional sampling data fusion using a Kalman filter has been implemented to fuse data gathered from different sources, connected through a wireless network (the vehicle's internal CAN bus messages, IMU, GPS, and other sensors placed in pedals). Our results show that the proposed combination of experimental data gathering and multi-rate filtering algorithm allows useful signal estimation for vehicle identification and modelling, even when data samples are missing

Structural invariance of multiple intelligences, based on the level of execution

The independence of multiple intelligences (MI) of Gardner’s theory has been debated since its conception. This article examines whether the one- factor structure of the MI theory tested in previous studies is invariant for low and high ability students. Two hundred ninety-four children (aged 5 to 7) participated in this study. A set of Gardner’s Multiple Intelligence assessment tasks based on the Spectrum Project was used. To analyze the invariance of a general dimension of intelligence, the different models of behaviours were studied in samples of participants with different performance on the Spectrum Project tasks with Multi-Group Confi rmatory Factor Analysis (MGCFA). Results suggest an absence of structural invariance in Gardner’s tasks. Exploratory analyses suggest a three-factor structure for individuals with higher performance levels and a two-factor structure for individuals with lower performance levels

The Mars Environmental Dynamics Analyzer, MEDA. A Suite of Environmental Sensors for the Mars 2020 Mission

86 pags, 49 figs, 24 tabsNASA's Mars 2020 (M2020) rover mission includes a suite of sensors to monitor current environmental conditions near the surface of Mars and to constrain bulk aerosol properties from changes in atmospheric radiation at the surface. The Mars Environmental Dynamics Analyzer (MEDA) consists of a set of meteorological sensors including wind sensor, a barometer, a relative humidity sensor, a set of 5 thermocouples to measure atmospheric temperature at ∼1.5 m and ∼0.5 m above the surface, a set of thermopiles to characterize the thermal IR brightness temperatures of the surface and the lower atmosphere. MEDA adds a radiation and dust sensor to monitor the optical atmospheric properties that can be used to infer bulk aerosol physical properties such as particle size distribution, non-sphericity, and concentration. The MEDA package and its scientific purpose are described in this document as well as how it responded to the calibration tests and how it helps prepare for the human exploration of Mars. A comparison is also presented to previous environmental monitoring payloads landed on Mars on the Viking, Pathfinder, Phoenix, MSL, and InSight spacecraft.This work has been funded by the Spanish Ministry of Economy and Competitiveness, through the projects No. ESP2014-54256-C4-1-R (also -2-R, -3-R and -4-R) and AYA2015-65041-P; Ministry of Science, Innovation and Universities, projects No. ESP2016-79612-C3-1-R (also -2-R and -3-R), ESP2016-80320-C2-1-R, RTI2018-098728-B-C31 (also -C32 and -C33) and RTI2018-099825-B-C31; Instituto Nacional de Tecnica Aeroespacial; Ministry of Science and Innovation's Centre for the Development of Industrial Technology; Grupos Gobierno Vasco IT1366-19; and European Research Council Consolidator Grant no 818602.Peer reviewe

Aprendizaje de políticas de control en robots manipuladores redundantes

En los últimos años ha surgido un nuevo movimiento en la robótica relacionado con el Aprendizaje por Demostración, que se espera que tome aún más fuerza en el futuro. En este proyecto se ha desarrollado un sistema que consigue enseñar una generalización de las trayectorias proporcionadas por el usuario a través de Modelos Mixtos Gaussianos. Para llegar hasta este aprendizaje se revisan varias técnicas de procesamiento y aprendizaje, comparando las diferencias entre los métodos empleados en cada caso. Además, todo ello se implementa en una Interfaz de Usuario que permite la simulación de datos en caso de no tener acceso al robot y la simplificación del uso del programa. Finalmente se pone en valor el conocimiento aprendido mediante la simulación de un control de fuerza y orientación que permite al robot el seguimiento de la trayectoria aprendida sobre superficies curvas continuas.In the last years a new movement has emerged in robotics related to Learning by Demonstration, which is expected to take even more part in the future. In this project a system that can train a generalization of the paths provided by the user has been developed using Gaussian Mixture Models. To reach this learning several processing and learning techniques are reviewed, comparing the differences between the methods used in every case. Moreover, all this is implemented in a User Interface that allows the simulation of data in case of not having access to the robot and the simplfication of the use of the program. Finally the knowledge learned is valued through the simulation of a force and orientation control that allows the robot to follow the path learned on continous curved surfaces.Hernández Ferrándiz, D. (2018). Aprendizaje de políticas de control en robots manipuladores redundantes. http://hdl.handle.net/10251/115539TFG

Teaching successful intelligence to gifted and talented students

The aim of this study is to analyze the theory of successful intelligence as a strategy to meet the educational needs of gifted and talented students. First, we present the theory of successful intelligence as an alternative that allows for an in-depth study of the cognitive complexity of high ability from a broader perspective of intelligence. Second, we analyze the roles of students and teachers in the learning-teaching process. Third, we indicate some learning strategies aimed at promoting the management of resources in the classroom related to the analytical, synthetic or creative and practical intelligence. Finally, some conclusions are drawn

Enseñanza de la inteligencia exitosa para alumnos superdotados y talentos

El objetivo del trabajo es analizar el modelo de la inteligencia exitosa como estrategia de desarrollo cognitivo para atender las necesidades educativas de los alumnos con altas habilidades. En primer lugar, exponemos la teoría de la inteligencia exitosa como alternativa en el estudio de la complejidad cognitiva de la alta habilidad desde una perspectiva más amplia de la inteligencia. En segundo lugar, se analizan los roles de alumno y profesor en el proceso de enseñanza-aprendizaje. En tercer lugar, se indican una serie de estrategias de aprendizaje orientadas a favorecer el manejo de recursos de la inteligencia académica, sintética y práctica en el aula. Finalmente, se extraen algunas conclusiones

The theory of multiple intelligences in the identification of high-ability students

This study provides a framework to implement the theory of multiple intelligences (MI) in the identification of high-ability students in secondary education. The internal structure of three scales to assess students' MI (students, parents and teachers' ratings) was analyzed in a sample of 566 students nominated as gifted by their teachers. Participants aged 11 to 16 years (M = 14.85, SD = 1.08). The results indicated differentiated intellectual profiles depending on the informant estimating students' MI. This study provided evidence for two components that allow us to analyze the cognitive competence of high-ability students beyond the areas commonly assessed at school: an academic component composed by the linguistic, logical-mathematical, naturalistic, and visual-spatial intelligences; and a non-academic component statistically loaded by the bodily-kinesthetic, musical and social intelligences. Convergence of the two components in the three scales was evidenced; and correlations between these components and students' objective performance on a psychometric intelligence test were found to be low. Finally, the utility of the MI scales to identify high-ability students in secondary education is discussed