Soft-computing based visual control for unmanned vehicles

El objetivo principal de esta Tesis es extender la utilización del “Soft- Computing” para el control de vehículos sin piloto utilizando visión. Este trabajo va más allá de los típicos sistemas de control utilizados en entornos altamente controlados, demonstrando la fuerza y versatilidad de la lógica difusa (Fuzzy Logic) para controlar vehículos aéreos y terrestres en un abanico de applicaciones diferentes. Para esta Tesis se ha realizado un gran número de pruebas reales en las cuales los controladores difusos han manejado una plataforma visual “pan-and-tilt”, un helicoptero, un coche comercial y hasta dos tipos de quadrirotores. El uso del método de optimización “Cross-Entropy” ha sido utilizado para mejorar el comportamiento de algunos de los controladores borrosos. Todos los controladores difusos presentados en ésta Tesis han sido implementados utilizando un código desarrollado por el candidato para tal efecto, llamado MOFS (Miguel Olivares’ Fuzzy Software). Diferentes algoritmos visuales han sido utilizados para adquirir la informaci´on visual del entorno, “Cmashift”, descomposición de la homografía y detección de marcas de realidad aumentada, entre otros. Dicha información visual ha sido utilizada como entrada de los controladores difusos para comandar los vehículos en las diferentes applicaciones autonomas. El volante de un vehículo comercial ha sido controlado para realizar pruebas de conducción autónoma en condiciones de tráfico similares a las de una ciudad. El sistema ha llegado a completar con éxito pruebas de más de 6 km sin ninguna interacción humana, mediante el seguimiento de una línea pintada en el suelo. El limitado campo visual del sistema no ha sido impedimento para alcanzar velocidades de hasta 48 km/h y ser guiado autonomamente en curvas de radio reducido. Objetos estáticos y móviles han sido seguidos desde un helicoptero no tripulado, mediante el control de una plataforma visual “pan-and-tilt”. ´Éste mismo helicoptero ha sido controlado completamente para su aterrizaje autonomo, mediante el control del movimiento lateral (roll), horizontal (pitch) y de altitud. El seguimiento de objetos volantes ha sido resulto mediante el control horizontal (pitch) y de orientación (heading) de un quadrirotor. Para tareas de evitación de obstáculos se ha implementado un controlador difuso para el manejo de la orientación (heading) de un quadrirotor. En el campo de la optimización de controladores se ha aportado al estado del arte una extensión del uso del método “Cross-Entropy”. Está Tesis presenta una novedosa implementación de dicho método para la optimización de las ganancias, la posición y medida de los conjuntos de las funciones de pertenecia y el peso de las reglas para mejorar el comportamiento de un controlador difuso. Dichos procesos de optimización se han realizado utilizando “ROS” y “Matlab Simulink” para obtener mejores resultados para la evitación de colisiones con vehículos aéreos no tripulados. Ésta Tesis demuestra que los controladores implementados con lógica difusa son altamente capaces de controlador sistemas sin tener en cuenta el modelo del vehículo a controlador en entornos altamente perturbables con un sensor de bajo coste como es una cámara. El ruido presentes causado por los cambios de iluminación en la adquisición de imágenes y la alta incertidumbre en la detección visual han sido manejados satisfactoriamente por ésta técnica de de “Soft-Computing” para distintas aplicaciones tanto con vehículos aéreos como terrestres

A pan-tilt camera Fuzzy vision controller on an unmanned aerial vehicle

is paper presents an implementation of two Fuzzy Logic controllers working in parallel for a pan-tilt camera platform on an UAV. This implementation uses a basic Lucas-Kanade tracker algorithm, which sends information about the error between the center of the object to track and the center of the image, to the Fuzzy controller. This information is enough for the controller, to follow the object moving a two axis servo-platform, besides the UAV vibrations and movements. The two Fuzzy controllers of each axis, work with a rules-base of 49 rules, two inputs and one output with a more significant sector defined to improve the behavior of those

Non-symmetric membership function for Fuzzy-based visual servoing onboard a UAV

This paper presents the definition of non-symmetric membership function for Fuzzy controllers applied to a pan & tilt vision platform onboard an Unmanned Aerial Vehicle. This improvement allows the controllers to have a more adaptive behavior to the non-linearities presented in an UAV. This implementation allows the UAV to follow objects in the environment by using Lucas-Kanade visual tracker, in spite of the aircraft vibrations, the movements of the objects and the aircraft. update has been tested in real flights with an unmanned helicopter of the Computer Vision Group at the UPM, with very successful results, attaining a considerable reduction of the error during the tracking tests

Fuzzy Controller for UAV-Landing Task Using 3D-Position Visual Estimation

This paper presents a Fuzzy Control application for a landing task of an Unmanned Aerial Vehicle, using the 3D-position estimation based on visual tracking of piecewise planar objects. This application allows the UAV to land on scenarios in which it is only possible to use visual information to obtain the position of the vehicle. The use of the homography permits a realtime estimation of the UAV's pose with respect to a helipad using a monocular camera. Fuzzy Logic allows the definition of a model-free control system of the UAV. The Fuzzy controller analyzes the visual information to generate altitude commands for the UAV to develop the landing task

3D pose estimation based on planar object tracking for UAVs control

This article presents a real time Unmanned Aerial Vehicles UAVs 3D pose estimation method using planar object tracking, in order to be used on the control system of a UAV. The method explodes the rich information obtained by a projective transformation of planar objects on a calibrated camera. The algorithm obtains the metric and projective components of a reference object (landmark or helipad) with respect to the UAV camera coordinate system, using a robust real time object tracking based on homographies. The algorithm is validated on real flights that compare the estimated data against that obtained by the inertial measurement unit IMU, showing that the proposed method robustly estimates the helicopter's 3D position with respect to a reference landmark, with a high quality on the position and orientation estimation when the aircraft is flying at low altitudes, a situation in which the GPS information is often inaccurate. The obtained results indicate that the proposed algorithm is suitable for complex control tasks, such as autonomous landing, accurate low altitude positioning and dropping of payloads

Visual servoing using fuzzy controllers on an unmanned aerial vehicles

This paper presents an implementa- tion of three Fuzzy Logic controllers working in parallel onboard a UAV, two for a pan-tilt camera platform and the third for control the yaw of the helicopter. This implementation uses a Lucas-Kanade tracker algo- rithm with a pyramidal optical ow implementation, which gives infor- mation to follow statics and moving objects, besides the UAV vibrations and movements. The platform con- troller is helped by the heading con- troller, in order to make smooth the big movements to the platform, re- ducing the risk of lost the warp selec- tion of the object to track. Also, the heading control remove the physic limit of the platform at the yaw axis. Some laboratory and UAV tests are presented in order to show the di er- ent behaviors and the good response of the presented controllers

3D Object following based on visual information for Unmanned Aerial Vehicles

This article presents a novel system and a control strategy for visual following of a 3D moving object by an Unmanned Aerial Vehicle UAV. The presented strategy is based only on the visual information given by an adaptive tracking method based on the color information, which jointly with the dynamics of a camera fixed to a rotary wind UAV are used to develop an Image-based visual servoing IBVS system. This system is focused on continuously following a 3D moving target object, maintaining it with a fixed distance and centered on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigatio

Aerial Object Following Using Visual Fuzzy Servoing

This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigatio

A Visual AGV-Urban Car using Fuzzy Control

The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just the visual information of a line painted below the car. In order to implement the control of the vehicle, a Fuzzy Logic controller has been implemented, that has to be robust against curvature changes and velocity changes. The only input information for the controller is the visual distance from the image center captured by a camera pointing downwards to the guiding line on the road, at a commercial frequency of 30Hz. The good performance of the controller has successfully been demonstrated in a real environment at urban velocities. The presented results demonstrate the capability of the Fuzzy controller to follow a circuit in urban environments without previous information about the path or any other information from additional sensor

A hierarchical strategy for real-time tracking on-board UAVs

In this paper, we present a real-time tracking strategy based on direct methods for tracking tasks on-board UAVs, that is able to overcome problems posed by the challenging conditions of the task: e.g. constant vibrations, fast 3D changes, and limited capacity on-board. The vast majority of approaches make use of feature-based methods to track objects. Nonetheless, in this paper we show that although some of these feature-based solutions are faster, direct methods can be more robust under fast 3D motions (fast changes in position), some changes in appearance, constant vibrations (without requiring any specific hardware or software for video stabilization), and situations where part of the object to track is out the field of view of the camera. The performance of the proposed strategy is evaluated with images from real-flight tests using different evaluation mechanisms (e.g. accurate position estimation using a Vicon sytem). Results show that our tracking strategy performs better than well known feature-based algorithms and well known configurations of direct methods, and that the recovered data is robust enough for vision-in-the-loop tasks