679 research outputs found

    Vision-based Global Path Planning and Trajectory Generation for Robotic Applications in Hazardous Environments

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    The aim of this study is to find an efficient global path planning algorithm and trajectory generation method using a vision system. Path planning is part of the more generic navigation function of mobile robots that consists of establishing an obstacle-free path, starting from the initial pose to the target pose in the robot workspace.In this thesis, special emphasis is placed on robotic applications in industrial and scientific infrastructure environments that are hazardous and inaccessible to humans, such as nuclear power plants and ITER1 and CERN2 LHC3 tunnel. Nuclear radiation can cause deadly damage to the human body, but we have to depend on nuclear energy to meet our great demands for energy resources. Therefore, the research and development of automatic transfer robots and manipulations under nuclear environment are regarded as a key technology by many countries in the world. Robotic applications in radiation environments minimize the danger of radiation exposure to humans. However, the robots themselves are also vulnerable to radiation. Mobility and maneuverability in such environments are essential to task success. Therefore, an efficient obstacle-free path and trajectory generation method are necessary for finding a safe path with maximum bounded velocities in radiation environments. High degree of freedom manipulators and maneuverable mobile robots with steerable wheels, such as non-holonomic omni-directional mobile robots make them suitable for inspection and maintenance tasks where the camera is the only source of visual feedback.In this thesis, a novel vision-based path planning method is presented by utilizing the artificial potential field, the visual servoing concepts and the CAD-based recognition method to deal with the problem of path and trajectory planning. Unlike the majority of conventional trajectory planning methods that consider a robot as only one point, the entire shape of a mobile robot is considered by taking into account all of the robot’s desired points to avoid obstacles. The vision-based algorithm generates synchronized trajectories for all of the wheels on omni-directional mobile robot. It provides the robot’s kinematic variables to plan maximum allowable velocities so that at least one of the actuators is always working at maximum velocity. The advantage of generated synchronized trajectories is to avoid slippage and misalignment in translation and rotation movement. The proposed method is further developed to propose a new vision-based path coordination method for multiple mobile robots with independently steerable wheels to avoid mutual collisions as well as stationary obstacles. The results of this research have been published to propose a new solution for path and trajectory generation in hazardous and inaccessible to human environments where the one camera is the only source of visual feedback

    Hardware, Software, and Low-Level Control Scheme Development for a Real-Time Autonomous Rover

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    The objective of this research is to develop a low-cost autonomous rover platform for experiments in autonomous navigation. This thesis describes the design, development, and testing of an autonomous rover platform, based on the commercial, off-the-shelf Tamiya TXT-1 radio controlled vehicle. This vehicle is outfitted with an onboard computer based on the Mini-ITX architecture and an array of sensors for localization and obstacle avoidance, and programmed with Matlab/SimulinkRTM Real-Time Workshop (RTW) utilizing the Linux Real-Time Application Interface (RTAI) operating system.;First, a kinematic model is developed and verified for the rover. Then a proportional-integral-derivative (PID) feedback controller is developed for translational and rotational velocity regulation. Finally, a hybrid navigation controller is developed combining a potential field controller and an obstacle avoidance controller for waypoint tracking.;Experiments are performed to verify the functionality of the kinematic model and the PID velocity controller, and to demonstrate the capabilities of the hybrid navigation controller. These experiments prove that the rover is capable of successfully navigating in an unknown indoor environment. Suggestions for future research include the integration of additional sensors for localization and creation of multiple platforms for autonomous coordination experiments

    Control and communication systems for automated vehicles cooperation and coordination

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    Mención Internacional en el título de doctorThe technological advances in the Intelligent Transportation Systems (ITS) are exponentially improving over the last century. The objective is to provide intelligent and innovative services for the different modes of transportation, towards a better, safer, coordinated and smarter transport networks. The Intelligent Transportation Systems (ITS) focus is divided into two main categories; the first is to improve existing components of the transport networks, while the second is to develop intelligent vehicles which facilitate the transportation process. Different research efforts have been exerted to tackle various aspects in the fields of the automated vehicles. Accordingly, this thesis is addressing the problem of multiple automated vehicles cooperation and coordination. At first, 3DCoAutoSim driving simulator was developed in Unity game engine and connected to Robot Operating System (ROS) framework and Simulation of Urban Mobility (SUMO). 3DCoAutoSim is an abbreviation for "3D Simulator for Cooperative Advanced Driver Assistance Systems (ADAS) and Automated Vehicles Simulator". 3DCoAutoSim was tested under different circumstances and conditions, afterward, it was validated through carrying-out several controlled experiments and compare the results against their counter reality experiments. The obtained results showed the efficiency of the simulator to handle different situations, emulating real world vehicles. Next is the development of the iCab platforms, which is an abbreviation for "Intelligent Campus Automobile". The platforms are two electric golf-carts that were modified mechanically, electronically and electrically towards the goal of automated driving. Each iCab was equipped with several on-board embedded computers, perception sensors and auxiliary devices, in order to execute the necessary actions for self-driving. Moreover, the platforms are capable of several Vehicle-to-Everything (V2X) communication schemes, applying three layers of control, utilizing cooperation architecture for platooning, executing localization systems, mapping systems, perception systems, and finally several planning systems. Hundreds of experiments were carried-out for the validation of each system in the iCab platform. Results proved the functionality of the platform to self-drive from one point to another with minimal human intervention.Los avances tecnológicos en Sistemas Inteligentes de Transporte (ITS) han crecido de forma exponencial durante el último siglo. El objetivo de estos avances es el de proveer de sistemas innovadores e inteligentes para ser aplicados a los diferentes medios de transporte, con el fin de conseguir un transporte mas eficiente, seguro, coordinado e inteligente. El foco de los ITS se divide principalmente en dos categorías; la primera es la mejora de los componentes ya existentes en las redes de transporte, mientras que la segunda es la de desarrollar vehículos inteligentes que hagan más fácil y eficiente el transporte. Diferentes esfuerzos de investigación se han llevado a cabo con el fin de solucionar los numerosos aspectos asociados con la conducción autónoma. Esta tesis propone una solución para la cooperación y coordinación de múltiples vehículos. Para ello, en primer lugar se desarrolló un simulador (3DCoAutoSim) de conducción basado en el motor de juegos Unity, conectado al framework Robot Operating System (ROS) y al simulador Simulation of Urban Mobility (SUMO). 3DCoAutoSim ha sido probado en diferentes condiciones y circunstancias, para posteriormente validarlo con resultados a través de varios experimentos reales controlados. Los resultados obtenidos mostraron la eficiencia del simulador para manejar diferentes situaciones, emulando los vehículos en el mundo real. En segundo lugar, se desarrolló la plataforma de investigación Intelligent Campus Automobile (iCab), que consiste en dos carritos eléctricos de golf, que fueron modificados eléctrica, mecánica y electrónicamente para darle capacidades autónomas. Cada iCab se equipó con diferentes computadoras embebidas, sensores de percepción y unidades auxiliares, con la finalidad de transformarlos en vehículos autónomos. Además, se les han dado capacidad de comunicación multimodal (V2X), se les han aplicado tres capas de control, incorporando una arquitectura de cooperación para operación en modo tren, diferentes esquemas de localización, mapeado, percepción y planificación de rutas. Innumerables experimentos han sido realizados para validar cada uno de los diferentes sistemas incorporados. Los resultados prueban la funcionalidad de esta plataforma para realizar conducción autónoma y cooperativa con mínima intervención humana.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Francisco Javier Otamendi Fernández de la Puebla.- Secretario: Hanno Hildmann.- Vocal: Pietro Cerr

    Experimental Testbed for Swarming and Cooperative Robotic Networks

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    This document describes an innovative cooperative robotics multi-vehicle testbed, featuring a flexible architecture that enables the system to be rapidly adapted to different applications. It also offers tools to reduce development and implementation time. The testbed consists of ten non-holonomic car-like robots networked together to share sensor information. Each vehicle features an on-board computer for local control, and a network of devices that can be suited with a variety of hot-swappable sensors depending on the application. The entire system is integrated with Player, an open source sensor server compatible with Gazebo, a 3D world simulator. Control algorithms can be evaluated in simulation mode and then ported to the real vehicle with virtually no code change. We present a flexible and complete system that serves the study of Cooperative Control, Hybrid and Embedded Systems, Sensor Networks, Networked Control and that can be used in an extensive range of applications.School of Electrical & Computer Engineerin

    A Framework for Coordinated Control of Multi-Agent Systems

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    Multi-agent systems represent a group of agents that cooperate to solve common tasks in a dynamic environment. Multi-agent control systems have been widely studied in the past few years. The control of multi-agent systems relates to synthesizing control schemes for systems which are inherently distributed and composed of multiple interacting entities. Because of the wide applications of multi-agent theories in large and complex control systems, it is necessary to develop a framework to simplify the process of developing control schemes for multi-agent systems. In this study, a framework is proposed for the distributed control and coordination of multi-agent systems. In the proposed framework, the control of multi-agent systems is regarded as achieving decentralized control and coordination of agents. Each agent is modeled as a Coordinated Hybrid Agent (CHA) which is composed of an intelligent coordination layer and a hybrid control layer. The intelligent coordination layer takes the coordination input, plant input and workspace input. After processing the coordination primitives, the intelligent coordination layer outputs the desired action to the hybrid layer. In the proposed framework, we describe the coordination mechanism in a domain-independent way, as simple abstract primitives in a coordination rule base for certain dependency relationships between the activities of different agents. The intelligent coordination layer deals with the planning, coordination, decision-making and computation of the agent. The hybrid control layer of the proposed framework takes the output of the intelligent coordination layer and generates discrete and continuous control signals to control the overall process. In order to verify the feasibility of the proposed framework, experiments for both heterogeneous and homogeneous Multi-Agent Systems (MASs) are implemented. In addition, the stability of systems modeled using the proposed framework is also analyzed. The conditions for asymptotic stability and exponential stability of a CHA system are given. In order to optimize a Multi-Agent System (MAS), a hybrid approach is proposed to address the optimization problem for a MAS modeled using the CHA framework. Both the event-driven dynamics and time-driven dynamics are included for the formulation of the optimization problem. A generic formula is given for the optimization of the framework. A direct identification algorithm is also discussed to solve the optimization problem

    Overcoming barriers and increasing independence: service robots for elderly and disabled people

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    This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

    Smooth and Collision-Free Navigation for Multiple Mobile Robots and Video Game Characters

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    The navigation of multiple mobile robots or virtual agents through environments containing static and dynamic obstacles to specified goal locations is an important problem in mobile robotics, many video games, and simulated environments. Moreover, technological advances in mobile robot hardware and video games consoles have allowed increasing numbers of mobile robots or virtual agents to navigate shared environments simultaneously. However, coordinating the navigation of large groups of mobile robots or virtual agents remains a difficult task. Kinematic and dynamic constraints and the effects of sensor and actuator uncertainty exaggerate the challenge of navigating multiple physical mobile robots, and video games players demand plausible motion and an ever increasing visual fidelity of virtual agents without sacrificing frame rate. We present new methods for navigating multiple mobile robots or virtual agents through shared environments, each using formulations based on velocity obstacles. These include algorithms that allow navigation through environments in two-dimensional or three-dimensional workspaces containing both static and dynamic obstacles without collisions or oscillations. Each mobile robot or virtual agent senses its surroundings and acts independently, without central coordination or inter-communication with its neighbors, implicitly assuming the neighbors use the same navigation strategy based on the notion of reciprocity. We use the position, velocity, and physical extent of neighboring mobile robots or virtual agents to compute their future trajectories to avoid collisions locally and show that, in principle, it is possible to theoretically guarantee that the motion of each mobile robot or virtual agent is smooth. Moreover, we demonstrate direct, collision-free, and oscillation-free navigation in experiments using physical iRobot Create mobile robots, simulations of multiple differential-drive robots or simple-airplanes, and video games levels containing hundreds of virtual agents.Doctor of Philosoph

    Unified Behavior Framework in an Embedded Robot Controller

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    Robots of varying autonomy have been used to take the place of humans in dangerous tasks. While robots are considered more expendable than human beings, they are complex to develop and expensive to replace if lost. Recent technological advances produce small, inexpensive hardware platforms that are powerful enough to match robots from just a few years ago. There are many types of autonomous control architecture that can be used to control these hardware platforms. One in particular, the Unified Behavior Framework, is a flexible, responsive control architecture that is designed to simplify the control system’s design process through behavior module reuse, and provides a means to speed software development. However, it has not been applied on embedded systems in robots. This thesis presents a development of the Unified Behavior Framework on the Mini-WHEGS™, a biologically inspired, embedded robotic platform. The Mini-WHEGS™ is a small robot that utilize wheel- legs to emulate cockroach walking patterns. Wheel-legs combine wheels and legs for high mobility without the complex control system required for legs. A color camera and a rotary encoder completes the robot, enabling the Mini-WHEGS™ to identify color objects and track its position. A hardware abstraction layer designed for the Mini-WHEGS™ in this configuration decouples the control system from the hardware and provide the interface between the software and the hardware. The result is a highly mobile embedded robot system capable of exchanging behavior modules with much larger robots while requiring little or no change to the modules

    Distributed control based on evolutionary game theory: multi-agent experiment

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    In this Master's thesis are applied distributed consensus and game theoretical algorithms to control a population of agents. The agents are embodies by Lego Mindstorm robots and controlled remotely with Bluetooth by the PC. Using a platform implemented in LabVIEW, which includes a camera and a pattern recognition tool, the robots are controlled to perform different tasks such as convergence to consensus position and formatio

    Mobile Robots Navigation

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    Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described
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