An Unsupervised Neural Network for Real-Time Low-Level Control of a Mobile Robot: Noise Resistance, Stability, and Hardware Implementation

We have recently introduced a neural network mobile robot controller (NETMORC). The controller is based on earlier neural network models of biological sensory-motor control. We have shown that NETMORC is able to guide a differential drive mobile robot to an arbitrary stationary or moving target while compensating for noise and other forms of disturbance, such as wheel slippage or changes in the robot's plant. Furthermore, NETMORC is able to adapt in response to long-term changes in the robot's plant, such as a change in the radius of the wheels. In this article we first review the NETMORC architecture, and then we prove that NETMORC is asymptotically stable. After presenting a series of simulations results showing robustness to disturbances, we compare NETMORC performance on a trajectory-following task with the performance of an alternative controller. Finally, we describe preliminary results on the hardware implementation of NETMORC with the mobile robot ROBUTER.Sloan Fellowship (BR-3122), Air Force Office of Scientific Research (F49620-92-J-0499

A Model of Operant Conditioning for Adaptive Obstacle Avoidance

We have recently introduced a self-organizing adaptive neural controller that learns to control movements of a wheeled mobile robot toward stationary or moving targets, even when the robot's kinematics arc unknown, or when they change unexpectedly during operation. The model has been shown to outperform other traditional controllers, especially in noisy environments. This article describes a neural network module for obstacle avoidance that complements our previous work. The obstacle avoidance module is based on a model of classical and operant conditioning first proposed by Grossberg ( 1971). This module learns the patterns of ultrasonic sensor activation that predict collisions as the robot navigates in an unknown cluttered environment. Along with our original low-level controller, this work illustrates the potential of applying biologically inspired neural networks to the areas of adaptive robotics and control.Office of Naval Research (N00014-95-1-0409, Young Investigator Award

Obstacle Avoidance by Means of an Operant Conditioning Model

This paper describes the application of a model of operant conditioning to the problem of obstacle avoidance with a wheeled mobile robot. The main characteristic of the applied model is that the robot learns to avoid obstacles through a learning-by-doing cycle without external supervision. A series of ultrasonic sensors act as Conditioned Stimuli (CS), while collisions act as an Unconditioned Stimulus (UCS). By experiencing a series of movements in a cluttered environment, the robot learns to avoid sensor activation patterns that predict collisions, thereby learning to avoid obstacles. Learning generalizes to arbitrary cluttered environments. In this work we describe our initial implementation using a computer simulation

Unsupervised Neural Network for the Control of a Mobile Robot

This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.Sloan Fellowship (BR-3122); Air Force Office of Scientific Research (F49620-92-J-0499

Robots para los ancianos

Producción CientíficaLos avances tecnológicos de los últimos años están favoreciendo la aparición de robots capaces de interaccionar con los humanos siguiendo reglas y comportamientos sociales, tal y como explica el artículo de National Geographic. El desarrollo de sistemas mecatrónicos con alta capacidad gestual, sistemas de reconocimiento de voz, agentes conversacionales y sistemas perceptivos basados en aprendizaje profundo hacen que cada vez estemos más cerca de relacionarnos con las máquinas de forma similar a como lo hacemos con otras personas. No obstante, los robots sociales aún tienen limitaciones, principalmente carencias perceptivas y cognitivas. Además, mientras que cualquier otro tipo de robot puede desarrollarse y validarse en el laboratorio, los robots sociales deben hacerlo en un entorno con humanos. La solución requiere la experimentación intensiva en entornos controlados, acotando inicialmente la funcionalidad para luego ir ampliando progresivamente el campo de aplicación. Una de sus funcionalidades más deseables es que contribuyan a combatir la soledad de los mayores y les ayuden a mantenerse activos física y mentalmente

Plataforma​ ​Robótica​ Para​ Tareas​ de​ Reconstrucción​ Tridimensional​ de​​ Entornos Exteriores

Este artículo presenta los resultados obtenidos en el diseño e implementación de una plataforma robótica todoterreno para la investigación y el desarrollo de aplicaciones de robótica de servicios en entornos exteriores, con especial énfasis en las tareas de reconstrucción tridimensional del entorno. En el documento se describe la estructura mecánica del robot, su arquitectura hardware-software y de comunicaciones y los sistemas perceptivos embarcados. Finalmente, como aportación adicional se presenta un algoritmo diseñado específicamente para llevar a cabo la reconstrucción tridimensional automática y eficiente del entorno, que opera sin necesidad de información previa sobre el mismo. Los resultados avalan la funcionalidad tanto de la plataforma robótica en sí, como de los algoritmos de adquisición y alineación de la información tridimensional, así como de selección automática de las mejores​ ​ posiciones​ ​ de​ ​ escaneo

Review of Display Technologies Focusing on Power Consumption

Producción CientíficaThis paper provides an overview of the main manufacturing technologies of displays, focusing on those with low and ultra-low levels of power consumption, which make them suitable for current societal needs. Considering the typified value obtained from the manufacturer’s specifications, four technologies—Liquid Crystal Displays, electronic paper, Organic Light-Emitting Display and Electroluminescent Displays—were selected in a first iteration. For each of them, several features, including size and brightness, were assessed in order to ascertain possible proportional relationships with the rate of consumption. To normalize the comparison between different display types, relative units such as the surface power density and the display frontal intensity efficiency were proposed. Organic light-emitting display had the best results in terms of power density for small display sizes. For larger sizes, it performs less satisfactorily than Liquid Crystal Displays in terms of energy efficiency.Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA036U14)Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA013A12-2)Ministerio de Economía, Industria y Competitividad (Grant DPI2014-56500-R

Algorithm for efficient 3D reconstruction of outdoor environments using mobile robots

In this paper, an algorithm for the reconstruction of an outdoor environment using a mobile robot is presented. The focus of this algorithm is making the mapping process efficient by capturing the greatest amount of information on every scan, ensuring at the same time that the overall quality of the resulting 3D model of the environment complies with the specified standards. With respect to existing approaches, the proposed approach is an innovation since there are very few information based methods for outdoor reconstruction that use resulting model quality and trajectory cost estimation as criteria for view planning

Optimization and improvement of a robotics gaze control system using LSTM networks

Producción CientíficaGaze control represents an important issue in the interaction between a robot and humans. Specifically, deciding who to pay attention to in a multi-party conversation is one way to improve the naturalness of a robot in human-robot interaction. This control can be carried out by means of two different models that receive the stimuli produced by the participants in an interaction, either an on-center off-surround competitive network or a recurrent neural network. A system based on a competitive neural network is able to decide who to look at with a smooth transition in the focus of attention when significant changes in stimuli occur. An important aspect in this process is the configuration of the different parameters of such neural network. The weights of the different stimuli have to be computed to achieve human-like behavior. This article explains how these weights can be obtained by solving an optimization problem. In addition, a new model using a recurrent neural network with LSTM layers is presented. This model uses the same set of stimuli but does not require its weighting. This new model is easier to train, avoiding manual configurations, and offers promising results in robot gaze control. The experiments carried out and some results are also presented.Ministerio de Ciencia, Innovación y Universidades (project TI2018-096652-B-I00)Junta de Castilla y León - Fondo Europeo de Desarrollo Regional (grant VA233P18

A bellboy robot: Study of the effects of robot behaviour on user engagement and comfort

Producción CientíficaThis paper provides the results of various trial experiments in a hotel environment carried out using Sacarino, an interactive bellboy robot. We analysed which aspects of the robot design and behaviour are relevant in terms of user engagement and comfort when interacting with our social robot. The experiments carried out focused on the influence over proxemics, duration and effectiveness of the interaction taking into account three dichotomous factors related with the robot design and behaviour: robot embodiment (with/without robotic body), status of the robot (awake/asleep) and who starts communication (robot/user). Results show that users tend to maintain a personal distance when interacting with an embodied robot and that embodiment engages users in maintaining longer interactions. On the other hand, including a greeting model in a robot is useful in terms of engaging users to maintain longer interactions, and that an active-looking robot is more attractive to the participants, producing longer interactions than in the case of a passive-looking robot.Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA036U14)Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA013A12-2)Ministerio de Economía, Industria y Competitividad (Grant DPI2014-56500-R