25 research outputs found
Contributions to Localization, Mapping and Navigation in Mobile Robotics
This thesis focuses on the problem of enabling mobile robots to autonomously build
world models of their environments and to employ them as a reference to self–localization
and navigation.
For mobile robots to become truly autonomous and useful, they must be able of
reliably moving towards the locations required by their tasks. This simple requirement
gives raise to countless problems that have populated research in the mobile robotics
community for the last two decades. Among these issues, two of the most relevant
are: (i) secure autonomous navigation, that is, moving to a target avoiding collisions
and (ii) the employment of an adequate world model for robot self-referencing within
the environment and also for locating places of interest. The present thesis introduces
several contributions to both research fields.
Among the contributions of this thesis we find a novel approach to extend SLAM
to large-scale scenarios by means of a seamless integration of geometric and topological
map building in a probabilistic framework that estimates the hybrid metric-topological
(HMT) state space of the robot path. The proposed framework unifies the research areas
of topological mapping, reasoning on topological maps and metric SLAM, providing
also a natural integration of SLAM and the “robot awakening” problem.
Other contributions of this thesis cover a wide variety of topics, such as optimal
estimation in particle filters, a new probabilistic observation model for laser scanners
based on consensus theory, a novel measure of the uncertainty in grid mapping, an
efficient method for range-only SLAM, a grounded method for partitioning large maps
into submaps, a multi-hypotheses approach to grid map matching, and a mathematical
framework for extending simple obstacle avoidance methods to realistic robots
Benchmarking Particle Filter Algorithms for Efficient Velodyne-Based Vehicle Localization
Keeping a vehicle well-localized within a prebuilt-map is at the core of any autonomous vehicle navigation system. In this work, we show that both standard SIR sampling and rejection-based optimal sampling are suitable for efficient (10 to 20 ms) real-time pose tracking without feature detection that is using raw point clouds from a 3D LiDAR. Motivated by the large amount of information captured by these sensors, we perform a systematic statistical analysis of how many points are actually required to reach an optimal ratio between efficiency and positioning accuracy. Furthermore, initialization from adverse conditions, e.g., poor GPS signal in urban canyons, we also identify the optimal particle filter settings required to ensure convergence. Our findings include that a decimation factor between 100 and 200 on incoming point clouds provides a large savings in computational cost with a negligible loss in localization accuracy for a VLP-16 scanner. Furthermore, an initial density of ∼2 particles/m 2 is required to achieve 100% convergence success for large-scale (∼100,000 m 2 ), outdoor global localization without any additional hint from GPS or magnetic field sensors. All implementations have been released as open-source software
A Low-Cost Modular Platform for Heterogeneous Data Acquisition with Accurate Interchannel Synchronization
Most experimental fields of science and engineering require the use of data
acquisition systems (DAQ), devices in charge of sampling and converting electrical signals into digital data and, typically, performing all of the required signal preconditioning. Since commercial DAQ systems are normally focused on specific types of sensors and actuators, systems engineers may need to employ mutually-incompatible hardware from
different manufacturers in applications demanding heterogeneous inputs and outputs, such as small-signal analog inputs, differential quadrature rotatory encoders or variable current
outputs. A common undesirable side effect of heterogeneous DAQ hardware is the lack
of an accurate synchronization between samples captured by each device. To solve such a
problem with low-cost hardware, we present a novel modular DAQ architecture comprising a base board and a set of interchangeable modules. Our main design goal is the ability to sample all sources at predictable, fixed sampling frequencies, with a reduced synchronization mismatch (<1 s) between heterogeneous signal sources. We present experiments in the field of mechanical engineering, illustrating vibration spectrum analyses from piezoelectric accelerometers and, as a novelty in these kinds of experiments, the spectrum of quadrature encoder signals. Part of the design and software will be publicly released online
A 3D Printed Power-Split Device for Testing Energy Management Strategies Applied to Hybrid Vehicles
This work presents a testbed emulating the hybrid electric vehicles powertrain with both teaching and research purposes. The core of this testbed is a 3D printed epicycloidal gearset actuating as a power split device. Its design and hardware equipment are explained as well as its working principle. From an educational point of view, this system states an interesting control problem and, at the same time, exemplifies the operation of this kind of machines with the scope of a motivating application. Consequently, a teaching methodology comprising this testbed is proposed. In addition, the challenging nature of the system encourage the development of optimization techniques aimed at reducing the overall system energy consumption. Results of a preliminary experiment are satisfactory addressed. As a consequence, the presented testbed is proposed as a remote lab for teaching and benchmarking new control strategies
A Factor-Graph-Based Approach to Vehicle Sideslip Angle Estimation
Sideslip angle is an important variable for understanding and monitoring vehicle dynamics, but there is currently no inexpensive method for its direct measurement. Therefore, it is typically estimated from proprioceptive sensors onboard using filtering methods from the family of the Kalman filter. As a novel alternative, this work proposes modeling the problem directly as a graphical model (factor graph), which can then be optimized using a variety of methods, such as whole-dataset batch optimization for offline processing or fixed-lag smoothing for on-line operation. Experimental results on real vehicle datasets validate the proposal, demonstrating a good agreement between estimated and actual sideslip angle, showing similar performance to state-of-the-art methods but with a greater potential for future extensions due to the more flexible mathematical framework. An open-source implementation of the proposed framework has been made available online
Soporte a tres alturas para equipos de medida de parámetros ambientales
Número de publicación: 2 661 542
Número de solicitud: 201600846
51 Int. CI.:
F16M 11/42 (2006.01)
B25H 1/10 (2006.01)Soporte para equipos de medida de parámetros
ambientales, del tipo de los que permiten la
colocación de equipos de medida en tres alturas y
ajustar dichas posiciones en altura. El soporte
incorpora un mástil (1) vertical y tres barras-soporte
(2) colocadas en posición horizontal y a distintas
alturas. Dichas barras-soporte (2) pueden
desplazarse verticalmente por medio de sus
respectivos mecanismos piñón-cremallera (3). El
mecanismo piñón-cremallera (3) incorpora un gatillo
(8) para evitar el desplazamiento de la barra-soporte
(2) debido a su propio peso. La barra-soporte (2)
presenta en toda su longitud una multitud de agujeros
(9) destinados a la ubicación de instrumentos de
medida.UNIVERSIDAD DE ALMERÍ
Distributed network for measuring climatic parameters in heterogeneous environments: Application in a greenhouse
In Mediterranean countries of Southern Europe, the climatic conditions are
usually favourable to cultivate greenhouse vegetables but not always for
workers. The aim of this study was to design a network of weather stations
capable of gathering data of environmental parameters related to the wellbeing
of workers in greenhouses in south-eastern Spain. The unevenness of the thermal
environment was studied both vertically as well as horizontally following
guideline ISO 7726. The results indicate that the greenhouse should be
considered a heterogeneous environment, implying that, for an evaluation of the
environmental conditions related to thermal stress of the workers inside the
greenhouse, measurements should be taken at different points within the
greenhouse at three heights (ankle, abdomen, and head).Comment: 47 pages, 15 figure
Medio de carga para máquinas de musculación
ES2617959 A1 (20.06.2017)
ES2617959 B2 (03.11.2017)
P201700130 (30.01.2017)Medio de carga del tipo de los utilizados en máquinas de musculación. El medio de carga incorpora dos guías curvas (1a, 1b) colocadas de forma simétrica y cuyas caras exteriores definen sendas pistas de rodadura (11a, 11b) sobre las que pueden desplazarse sendos rodillos (3a, 3b). Los ejes (4a, 4b) de dichos rodillos (3a, 3b) están unidos entre sí mediante un resorte de extensión (5). Dos tirantes (6a, 6b) unen los ejes (4a, 4b) de sendos rodillos (3a, 3b) con un cable de carga (8). La geometría de la curva definida por las pistas de rodadura (11a, 11b) es tal que la fuerza exterior aplicada sobre el cable de carga (8) es la misma independientemente de la posición en la que se encuentren los rodillos (3a, 3b).UNIVERSIDAD DE ALMERÍ
Uncertainty-Aware Calibration of a Hot-Wire Anemometer With Gaussian Process Regression
Expensive ultrasonic anemometers are usually required to measure wind speed
accurately. The aim of this work is to overcome the loss of accuracy of a low
cost hot-wire anemometer caused by the changes of air temperature, by means of
a probabilistic calibration using Gaussian Process Regression. Gaussian Process
Regression is a non-parametric, Bayesian, and supervised learning method
designed to make predictions of an unknown target variable as a function of one
or more known input variables. Our approach is validated against real datasets,
obtaining a good performance in inferring the actual wind speed values. By
performing, before its real use in the field, a calibration of the hot-wire
anemometer taking into account air temperature, permits that the wind speed can
be estimated for the typical range of ambient temperatures, including a
grounded uncertainty estimation for each speed measure.Comment: 10 pages, 6 figures, Published in "IEEE Sensors Journal