Control de orientación de un vehículo aéreo no tripulado de ala fija

Este artículo aborda el problema del control de la orientación de un UAV de ala fija. Con este fin, se obtiene un modelo dinámico completo que describe el comportamiento del vehículo. Posteriormente, se utiliza la técnica de control quasicontinuo por sus atractivas propiedades, tales como robustez y convergencia en tiempo finito. Con el objetivo de implementar dicho controlador, un diferenciador robusto se emplea para estimar las derivadas de la superficie deslizante. El esquema de control propuesto es capaz de controlar el UAV de ala fija, bajo perturbaciones externas y dinámica acoplada. Los resultados en simulación demuestran el buen desempeño del esquema de control propuesto

Computing Pressure-Deformation Maps for Braided Continuum Robots

This paper presents a method for computing sensorimotor maps of braided continuum robots driven by pneumatic actuators. The method automatically creates a lattice-like representation of the sensorimotor map that preserves the topology of the input space by arranging its nodes into clusters of related data. Deformation trajectories can be simply represented with adjacent nodes whose values smoothly change along the lattice curve; this facilitates the computation of controls and the prediction of deformations in systems with unknown mechanical properties. The proposed model has an adaptive structure that can recalibrate to cope with changes in the mechanism or actuators. An experimental study with a robotic prototype is conducted to validate the proposed method

A Parallel Robotic Antenna Design for Downlinking Leo Satellite Signal Subject to Wind Disturbance

Passive LEO (Low Earth Orbit) satellites are a telecom premier option. However, LEO satellites impose not only stringent specifications on the resolution, precision and repeatability but also requiring advanced antenna technology for signal downlinking. To efficiently downlink LEO signals at each passage onto a given Earth region, we explored large size passive Earth antenna and an array of smaller size active Earth antennas to minimize the trajectory loss. To guarantee design specifications, the dynamics cannot be neglected given the size and inertia of base and antenna. In this paper, it is proposed the design, path planning and control of a six DoF robotic antenna maneuvering the antenna subject to aerodynamic wind disturbance. The system maneuvers to point at the LEO satellite over the whole envelope with the required precision to guarantee robust point-to-point tracking. Representative simulation results for three geolocations shows practical tracking with off-the-shelf-component actuators, without requiring any knowledge of the dynamics while withstanding state-dependent persistent disturbances

A Parallel Robotic Antenna Design for Downlinking Leo Satellite Signal Subject to Wind Disturbance

Passive LEO (Low Earth Orbit) satellites are a telecom premier option. However, LEO satellites impose not only stringent specifications on the resolution, precision and repeatability but also requiring advanced antenna technology for signal downlinking. To efficiently downlink LEO signals at each passage onto a given Earth region, we explored large size passive Earth antenna and an array of smaller size active Earth antennas to minimize the trajectory loss. To guarantee design specifications, the dynamics cannot be neglected given the size and inertia of base and antenna. In this paper, it is proposed the design, path planning and control of a six DoF robotic antenna maneuvering the antenna subject to aerodynamic wind disturbance. The system maneuvers to point at the LEO satellite over the whole envelope with the required precision to guarantee robust point-to-point tracking. Representative simulation results for three geolocations shows practical tracking with off-the-shelf-component actuators, without requiring any knowledge of the dynamics while withstanding state-dependent persistent disturbances

Vision-Based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions Using a Model-Free Robust Control

This paper presents a vision-based navigation system for an autonomous underwater vehicle in semistructured environments with poor visibility. In terrestrial and aerial applications, the use of visual systems mounted in robotic platforms as a control sensor feedback is commonplace. However, robotic vision-based tasks for underwater applications are still not widely considered as the images captured in this type of environments tend to be blurred and/or color depleted. To tackle this problem, we have adapted the lαβ color space to identify features of interest in underwater images even in extreme visibility conditions. To guarantee the stability of the vehicle at all times, a model-free robust control is used. We have validated the performance of our visual navigation system in real environments showing the feasibility of our approach