Diseño e implementación software de un robot humanoide.

[ES]Este documento tiene la intención de presentar un Trabajo de Fin de Grado (TFG). Este proyecto consiste en una serie de herramientas que permitan el diseño, implementación y desarrollo del software de control de un robot humanoide. El proyecto se centra en la mejora de la efectividad, robustez, rendimiento y fiabilidad del software. Los cambios propuestos introducen mejoras sobre el robot comercial robo nova. En concreto la capacidad de ser modular, permitiendo de esta forma el uso total o parcial de las soluciones escogidas, ahorrando tiempo y dinero en futuros desarrollos de esta plataforma

Implementación hardware de un robot humanoide.

[ES]Este trabajo describe una serie de mejoras aplicables a un kit comercial de robot humanoide Robonova, con el fin de que este reproduzca el comportamiento cinemático del ser humano con mayor autonomía. Entre ellas destacan la implementación de sensores infrarrojos, sensores de posición, cámaras de visión y conexiones en serie de servomotores. Todo ello controlado desde un ordenador de placa reducida Raspberry Pi.

Modeling Innovative Power Take-Off Based on Double-Acting Hydraulic Cylinders Array for Wave Energy Conversion

One of the key systems of a Wave Energy Converter for extraction of wave energy is the Power Take-Off (PTO) device. This device transforms the mechanical energy of a moving body into electrical energy. This paper describes the model of an innovative PTO based on independently activated double-acting hydraulic cylinders array. The model has been developed using a simulation tool, based on a port-based approach to model hydraulics systems. The components and subsystems used in the model have been parameterized as real components and their values experimentally obtained from an existing prototype. In fact, the model takes into account most of the hydraulic losses of each component. The simulations show the flexibility to apply different restraining torques to the input movement depending on the geometrical configuration and the hydraulic cylinders on duty, easily modified by a control law. The combination of these two actions allows suitable flexibility to adapt the device to different sea states whilst optimizing the energy extraction. The model has been validated using a real test bench showing good correlations between simulation and experimental tests.

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.