Improving Mobile Robot Maneuver Performance Using Fractional-Order Controller.

In this paper, the low-level velocity controller of an autonomous vehicle is studied. The performance of the traditional controller used in this kind of system, a PID, is analyzed. This kind of controller cannot follow ramp references without error, so when the reference implies a change in the speed, the vehicle cannot follow the proposed reference, and there is a significant difference between the actual and desired vehicle behaviors. A fractional controller is proposed which changes the ordinary dynamics allowing faster responses for small times, at the cost of slower responses for large times. The idea is to take advantage of this fact to follow fast setpoint changes with a smaller error than that obtained with a classic non-fractional PI controller. Using this controller, the vehicle can follow variable speed references with zero stationary error, significantly reducing the difference between reference and actual vehicle behavior. The paper presents the fractional controller, studies its stability in function of the fractional parameters, designs the controller, and tests its stability. The designed controller is tested on a real prototype, and its behavior is compared to a standard PID controller. The designed fractional PID controller overcomes the results of the standard PID controller.

Improving Odometric Model Performance Based on LSTM Networks.

This paper presents a localization system for an autonomous wheelchair that includes several sensors, such as odometers, LIDARs, and an IMU. It focuses on improving the odometric localization accuracy using an LSTM neural network. Improved odometry will improve the result of the localization algorithm, obtaining a more accurate pose. The localization system is composed by a neural network designed to estimate the current pose using the odometric encoder information as input. The training is carried out by analyzing multiple random paths and defining the velodyne sensor data as training ground truth. During wheelchair navigation, the localization system retrains the network in real time to adjust any change or systematic error that occurs with respect to the initial conditions. Furthermore, another network manages to avoid certain random errors by using the relationship between the power consumed by the motors and the actual wheel speeds. The experimental results show several examples that demonstrate the ability to self-correct against variations over time, and to detect non-systematic errors in different situations using this relation. The final robot localization is improved with the designed odometric model compared to the classic robot localization based on sensor fusion using a static covariance.

Calibration of a Stereoscopic Vision System in the Presence of Errors in Pitch Angle.

This paper proposes a novel method for the calibration of a stereo camera system used to reconstruct 3D scenes. An error in the pitch angle of the cameras causes the reconstructed scene to exhibit some distortion with respect to the real scene. To do the calibration procedure, whose purpose is to eliminate or at least minimize said distortion, machine learning techniques have been used, and more specifically, regression algorithms. These algorithms are trained with a large number of vectors of input features with their respective outputs, since, in view of the application of the procedure proposed, it is important that the training set be sufficiently representative of the variety that can occur in a real scene, which includes the different orientations that the pitch angle can take, the error in said angle and the effect that all this has on the reconstruction process. The most efficient regression algorithms for estimating the error in the pitch angle are derived from decision trees and certain neural network configurations. Once estimated, the error can be corrected, thus making the reconstructed scene appear more like the real one. Although the authors base their method on U-V disparity and employ this same technique to completely reconstruct the 3D scene, one of the most interesting features of the method proposed is that it can be applied regardless of the technique used to carry out said reconstruction.

Influence of Pitch Angle Errors in 3D Scene Reconstruction Based on U-V Disparity: A Sensitivity Study.

U-V disparity is a technique that is commonly used to detect obstacles in 3D scenes, modeling them as a set of vertical planes. In this paper, the authors describe the general lines of a method based on this technique for fully reconstructing 3D scenes, and conduct an analytical study of its performance and sensitivity to errors in the pitch angle of the stereoscopic vision system. The equations of the planes calculated for a given error in this angle yield the deviation with respect to the ideal planes (with a zero error in the angle) for a large test set consisting of planes with different orientations, which is represented graphically to analyze the method's qualitative and quantitative performance. The relationship between the deviation of the planes and the error in the pitch angle is observed to be linear. Two major conclusions are drawn from this study: first, that the deviation between the calculated and ideal planes is always less than or equal to the error considered in the pitch angle; and second, that even though in some cases the deviation of the plane is zero or very small, the probability that a plane of the scene deviates from the ideal by the greatest amount possible, which matches the error in the pitch angle, is very high.

Improving Robot Localization Using Doppler-Based Variable Sensor Covariance Calculation.

This paper describes a localization module for an autonomous wheelchair. This module includes a combination of various sensors such as odometers, laser scanners, IMU and Doppler speed sensors. Every sensor used in the module features variable covariance estimation in order to yield a final accurate localization. The main problem of a localization module composed of different sensors is the accuracy estimation of each sensor. Average static values are normally used, but these can lead to failure in some situations. In this paper, all the sensors have a variable covariance estimation that depends on the data quality. A Doppler speed sensor is used to estimate the covariance of the encoder odometric localization. Lidar is also used as a scan matching localization algorithm, comparing the difference between two consecutive scans to obtain the change in position. Matching quality gives the accuracy of the scan matcher localization. This structure yields a better position than a traditional odometric static covariance method. This is tested in a real prototype and compared to a standard fusion technique.

Manejo endovascular de fístula arteriovenosa postraumática / Endovascular management of post-traumatic arteriovenous fistula

Resumen Objetivos Reportar un caso de fístula arteriovenosa crónica como una complicación tardía por una herida de arma de fuego, la cual se manejó con colocación de una endoprótesis recubierta en arteria femoral. Diseño Se tomaron imágenes y el registro del Hospital Central Militar para reportar el caso clínico. En el siguiente artículo describimos la experiencia del Hospital Central Militar en el tratamiento de la fístula arteriovenosa crónica con el manejo endovascular.

Abstract Objectives To report a case of chronic arteriovenous fistula as a late complication of a gunshot wound, which was managed with a covered stent placement in the femoral artery. Design Images and records were taken from the Central Military Hospital to report the clinical case. In the following article, we describe the experience of the Central Military Hospital in the treatment of a chronic arteriovenous fistula with en endovascular management.

Improving Odometric Accuracy for an Autonomous Electric Cart.

In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.

Fast Object Motion Estimation Based on Dynamic Stixels.

The stixel world is a simplification of the world in which obstacles are represented as vertical instances, called stixels, standing on a surface assumed to be planar. In this paper, previous approaches for stixel tracking are extended using a two-level scheme. In the first level, stixels are tracked by matching them between frames using a bipartite graph in which edges represent a matching cost function. Then, stixels are clustered into sets representing objects in the environment. These objects are matched based on the number of stixels paired inside them. Furthermore, a faster, but less accurate approach is proposed in which only the second level is used. Several configurations of our method are compared to an existing state-of-the-art approach to show how our methodology outperforms it in several areas, including an improvement in the quality of the depth reconstruction.

El uso combinado de la exposición a realidad virtual en el tratamiento de la agorafobia / The combined use of virtual reality exposure in the treatment of agoraphobia

Introducción. Este estudio compara la eficacia diferencia de tres grupos de tratamiento para la agorafobia: paroxetina en combinación con terapia cognitivo-conductual, paroxetina en combinación con terapia cognitivo-conductual y exposición de realidad virtual, y un grupo sólo con paroxetina. Metodología. Fueron seleccionados 99 pacientes con agorafobia. Ambos grupos de tratamiento combinado recibieron 11 sesiones de terapia cognitivo-conductual y uno de los grupos también fue expuesto a 4 sesiones de tratamiento de realidad virtual. Los tratamientos se aplicaron en sesiones individuales una vez a la semana durante 3 meses. Resultados. Los tres grupos de tratamiento mostraron mejoras estadísticamente significativas. En algunas de las medidas, los grupos de tratamiento combinado mostraron mayores mejoras y el grupo tratado con la exposición de realidad virtual mostró una mayor capacidad de enfrentar los estímulos fóbicos. Conclusiones. Los tratamientos que combinaron terapia psicofarmacológica y psicológica mostraron una mayor eficacia. Aunque el uso de las nuevas tecnologías dio lugar a una mejoría mayor, siguen existiendo problemas relacionados con la adherencia al tratamiento

Introduction. This study compares the differential efficacy of three groups of treatments for agoraphobia: paroxetine combined with cognitive-behavioral therapy, paroxetine combined with cognitive-behavioral therapy and virtual reality exposure, and a group with only paroxetine. Methodology. 99 patients with agoraphobia were finally selected. Both combined treatment groups received 11 sessions of cognitive-behavioral therapy, and one of the groups was also exposed to 4 sessions of virtual reality treatment. Treatments were applied in individual sessions once a week for 3 months. Results. The three treatment groups showed statistically significant improvements. In some measures, combined treatment groups showed greater improvements. The virtual reality exposure group showed greater improvement confronting phobic stimuli. Conclusions. Treatments combining psychopharmacological and psychological therapy showed greater efficacy. Although the use of new technologies led to greater improvement, treatment adherence problems still remain

The combined use of virtual reality exposure in the treatment of agoraphobia.

INTRODUCTION: This study compares the differential efficacy of three groups of treatments for agoraphobia: paroxetine combined with cognitive-behavioral therapy, paroxetine combined with cognitive-behavioral therapy and virtual reality exposure, and a group with only paroxetine. METHODOLOGY: 99 patients with agoraphobia were finally selected. Both combined treatment groups received 11 sessions of cognitive-behavioral therapy, and one of the groups was also exposed to 4 sessions of virtual reality treatment. Treatments were applied in individual sessions once a week for 3 months. RESULTS: The three treatment groups showed statistically significant improvements. In some measures, combined treatment groups showed greater improvements. The virtual reality exposure group showed greater improvement confronting phobic stimuli. CONCLUSIONS: Treatments combining psychopharmacological and psychological therapy showed greater efficacy. Although the use of new technologies led to greater improvement, treatment adherence problems still remain.

Application of time dependent probabilistic collision state checkers in highly dynamic environments.

When computing the trajectory of an autonomous vehicle, inevitable collision states must be avoided at all costs, so no harm comes to the device or pedestrians around it. In dynamic environments, considering collisions as binary events is risky and inefficient, as the future position of moving obstacles is unknown. We introduce a time-dependent probabilistic collision state checker system, which traces a safe route with a minimum collision probability for a robot. We apply a sequential Bayesian model to calculate approximate predictions of the movement patterns of the obstacles, and define a time-dependent variation of the Dijkstra algorithm to compute statistically safe trajectories through a crowded area. We prove the efficiency of our methods through experimentation, using a self-guided robotic device.

Fusion of a variable baseline system and a range finder.

One of the greatest difficulties in stereo vision is the appearance of ambiguities when matching similar points from different images. In this article we analyze the effectiveness of using a fusion of multiple baselines and a range finder from a theoretical point of view, focusing on the results of using both prismatic and rotational articulations for baseline generation, and offer a practical case to prove its efficiency on an autonomous vehicle.

Asphalted road temperature variations due to wind turbine cast shadows.

The contribution of this paper is a technique that in certain circumstances allows one to avoid the removal of dynamic shadows in the visible spectrum making use of images in the infrared spectrum. This technique emerged from a real problem concerning the autonomous navigation of a vehicle in a wind farm. In this environment, the dynamic shadows cast by the wind turbines' blades make it necessary to include a shadows removal stage in the preprocessing of the visible spectrum images in order to avoid the shadows being misclassified as obstacles. In the thermal images, dynamic shadows completely disappear, something that does not always occur in the visible spectrum, even when the preprocessing is executed. Thus, a fusion on thermal and visible bands is performed.

A neuro-fuzzy system for extracting environment features based on ultrasonic sensors.

In this paper, a method to extract features of the environment based on ultrasonic sensors is presented. A 3D model of a set of sonar systems and a workplace has been developed. The target of this approach is to extract in a short time, while the vehicle is moving, features of the environment. Particularly, the approach shown in this paper has been focused on determining walls and corners, which are very common environment features. In order to prove the viability of the devised approach, a 3D simulated environment has been built. A Neuro-Fuzzy strategy has been used in order to extract environment features from this simulated model. Several trials have been carried out, obtaining satisfactory results in this context. After that, some experimental tests have been conducted using a real vehicle with a set of sonar systems. The obtained results reveal the satisfactory generalization properties of the approach in this case.

Distance and cable length measurement system.

A simple, economic and successful design for distance and cable length detection is presented. The measurement system is based on the continuous repetition of a pulse that endlessly travels along the distance to be detected. There is a pulse repeater at both ends of the distance or cable to be measured. The endless repetition of the pulse generates a frequency that varies almost inversely with the distance to be measured. The resolution and distance or cable length range could be adjusted by varying the repetition time delay introduced at both ends and the measurement time. With this design a distance can be measured with centimeter resolution using electronic system with microsecond resolution, simplifying classical time of flight designs which require electronics with picosecond resolution. This design was also applied to position measurement.

Técnica quirúrgica de transplante segmentario pancreático autólogo en perros. Modelo experimental / Surgical technique of autologous segmentary prancreatic transplant in dogs. An experimental model

El trasplante segmentario autólogo de páncreas ha servido como base de diversos estudios. En este trabajo se sometieron a 20 perros a este tipo de cirugía, en la fase de práctica y 13 en el grupo experimental, monitorizándolos por medio de glicemia y biopsia del órgano transplantado. La sobrevida fue del 85 por ciento. Las glucosas preoperatoria y postoperatoria se compararon siendo p<0.05. Los resultados histopatológicos demostraron alteraciones mínimas, siendo normales la mayoría de los óranos injertados. Este modelo experimental puede servir de base para futuros proyectados de transplante de páncreas, ya que resultó práctico y reproducible, y su desarrollo adecuado puede ser evaluado por medio de la toma de glicemias y biopsia