Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Mobile Robots Navigation

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

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Automation and robotics for the Space Exploration Initiative: Results from Project Outreach

A total of 52 submissions were received in the Automation and Robotics (A&R) area during Project Outreach. About half of the submissions (24) contained concepts that were judged to have high utility for the Space Exploration Initiative (SEI) and were analyzed further by the robotics panel. These 24 submissions are analyzed here. Three types of robots were proposed in the high scoring submissions: structured task robots (STRs), teleoperated robots (TORs), and surface exploration robots. Several advanced TOR control interface technologies were proposed in the submissions. Many A&R concepts or potential standards were presented or alluded to by the submitters, but few specific technologies or systems were suggested

Visually guided obstacle detection and avoidance for legged robot.

Chow Ying-ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 78-83).Abstracts in English and Chinese.Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Objectives - Visual Navigation for Legged Robots --- p.1Chapter 1.2 --- Summary of Results --- p.3Chapter 1.3 --- Hardware Issues --- p.4Chapter 1.4 --- Contributions --- p.4Chapter 1.5 --- Organization of the Thesis --- p.4Chapter Chapter 2 --- Previous Work --- p.6Chapter 2.1 --- Vision Based Navigation --- p.6Chapter 2.1.1 --- Homography --- p.7Chapter 2.1.2 --- Ground Plane Obstacle Detection --- p.9Chapter 2.1.3 --- Regression --- p.12Chapter 2.2 --- Control Strategy --- p.13Chapter Chapter 3 --- System Overview --- p.16Chapter Chapter 4 --- Obstacle Detection by Fast Homography Estimation --- p.20Chapter 4.1 --- Ground Feature Extraction --- p.21Chapter 4.2 --- Ground Feature Correspondence --- p.21Chapter 4.3 --- Ground Homography Estimation --- p.24Chapter 4.3.1 --- Input point transformation --- p.24Chapter 4.3.2 --- Initial estimation --- p.26Chapter 4.3.3 --- Robust estimation --- p.27Chapter 4.4 --- Obstacle Detection --- p.29Chapter 4.5 --- Local Obstacle Map (LOM) on Ground --- p.33Chapter 4.5.1 --- Extraction from accumulative evidence --- p.34Chapter 4.5.2 --- Time-delay compensation --- p.34Chapter Chapter 5 --- Obstacle Avoidance by a Fuzzy Controller --- p.36Chapter 5.1 --- Gait Pattern --- p.38Chapter 5.2 --- Fuzzy Logic Controller --- p.42Chapter 5.2.1 --- Controller Inputs --- p.42Chapter 5.2.2 --- Controller Outputs --- p.43Chapter 5.2.3 --- Inference mechanism --- p.46Chapter Chapter 6 --- Implementation --- p.49Chapter 6.1 --- Hardware components --- p.49Chapter 6.1.1 --- VisionBug --- p.49Chapter 6.1.2 --- RF transmitter / receiver modules: --- p.52Chapter 6.2 --- Perception --- p.55Chapter 6.3 --- Image Calibration --- p.56Chapter 6.4 --- Motion Calibration: --- p.58Chapter 6.5 --- Software Programs --- p.66Chapter 6.5.1 --- Computational complexity --- p.68Chapter Chapter 7 --- Experimental Results --- p.69Chapter 7.1 --- Real Navigation Experiments --- p.70Chapter 7.2 --- Error Analysis of LOM --- p.73Chapter Chapter 8 --- Conclusion and future work --- p.7

Adaptive Robot Framework: Providing Versatility and Autonomy to Manufacturing Robots Through FSM, Skills and Agents

207 p.The main conclusions that can be extracted from an analysis of the current situation and future trends of the industry,in particular manufacturing plants, are the following: there is a growing need to provide customization of products, ahigh variation of production volumes and a downward trend in the availability of skilled operators due to the ageingof the population. Adapting to this new scenario is a challenge for companies, especially small and medium-sizedenterprises (SMEs) that are suffering first-hand how their specialization is turning against them.The objective of this work is to provide a tool that can serve as a basis to face these challenges in an effective way.Therefore the presented framework, thanks to its modular architecture, allows focusing on the different needs of eachparticular company and offers the possibility of scaling the system for future requirements. The presented platform isdivided into three layers, namely: interface with robot systems, the execution engine and the application developmentlayer.Taking advantage of the provided ecosystem by this framework, different modules have been developed in order toface the mentioned challenges of the industry. On the one hand, to address the need of product customization, theintegration of tools that increase the versatility of the cell are proposed. An example of such tools is skill basedprogramming. By applying this technique a process can be intuitively adapted to the variations or customizations thateach product requires. The use of skills favours the reuse and generalization of developed robot programs.Regarding the variation of the production volumes, a system which permits a greater mobility and a faster reconfigurationis necessary. If in a certain situation a line has a production peak, mechanisms for balancing the loadwith a reasonable cost are required. In this respect, the architecture allows an easy integration of different roboticsystems, actuators, sensors, etc. In addition, thanks to the developed calibration and set-up techniques, the system canbe adapted to new workspaces at an effective time/cost.With respect to the third mentioned topic, an agent-based monitoring system is proposed. This module opens up amultitude of possibilities for the integration of auxiliary modules of protection and security for collaboration andinteraction between people and robots, something that will be necessary in the not so distant future.For demonstrating the advantages and adaptability improvement of the developed framework, a series of real usecases have been presented. In each of them different problematic has been resolved using developed skills,demonstrating how are adapted easily to the different casuistic

Percepción basada en visión estereoscópica, planificación de trayectorias y estrategias de navegación para exploración robótica autónoma

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería del Software e Inteligencia artificial, leída el 13-05-2015En esta tesis se trata el desarrollo de una estrategia de navegación autónoma basada en visión artificial para exploración robótica autónoma de superficies planetarias. Se han desarrollado una serie de subsistemas, módulos y software específicos para la investigación desarrollada en este trabajo, ya que la mayoría de las herramientas existentes para este dominio son propiedad de agencias espaciales nacionales, no accesibles a la comunidad científica. Se ha diseñado una arquitectura software modular multi-capa con varios niveles jerárquicos para albergar el conjunto de algoritmos que implementan la estrategia de navegación autónoma y garantizar la portabilidad del software, su reutilización e independencia del hardware. Se incluye también el diseño de un entorno de trabajo destinado a dar soporte al desarrollo de las estrategias de navegación. Éste se basa parcialmente en herramientas de código abierto al alcance de cualquier investigador o institución, con las necesarias adaptaciones y extensiones, e incluye capacidades de simulación 3D, modelos de vehículos robóticos, sensores, y entornos operacionales, emulando superficies planetarias como Marte, para el análisis y validación a nivel funcional de las estrategias de navegación desarrolladas. Este entorno también ofrece capacidades de depuración y monitorización.La presente tesis se compone de dos partes principales. En la primera se aborda el diseño y desarrollo de las capacidades de autonomía de alto nivel de un rover, centrándose en la navegación autónoma, con el soporte de las capacidades de simulación y monitorización del entorno de trabajo previo. Se han llevado a cabo un conjunto de experimentos de campo, con un robot y hardware real, detallándose resultados, tiempo de procesamiento de algoritmos, así como el comportamiento y rendimiento del sistema en general. Como resultado, se ha identificado al sistema de percepción como un componente crucial dentro de la estrategia de navegación y, por tanto, el foco principal de potenciales optimizaciones y mejoras del sistema. Como consecuencia, en la segunda parte de este trabajo, se afronta el problema de la correspondencia en imágenes estéreo y reconstrucción 3D de entornos naturales no estructurados. Se han analizado una serie de algoritmos de correspondencia, procesos de imagen y filtros. Generalmente se asume que las intensidades de puntos correspondientes en imágenes del mismo par estéreo es la misma. Sin embargo, se ha comprobado que esta suposición es a menudo falsa, a pesar de que ambas se adquieren con un sistema de visión compuesto de dos cámaras idénticas. En consecuencia, se propone un sistema experto para la corrección automática de intensidades en pares de imágenes estéreo y reconstrucción 3D del entorno basado en procesos de imagen no aplicados hasta ahora en el campo de la visión estéreo. Éstos son el filtrado homomórfico y la correspondencia de histogramas, que han sido diseñados para corregir intensidades coordinadamente, ajustando una imagen en función de la otra. Los resultados se han podido optimizar adicionalmente gracias al diseño de un proceso de agrupación basado en el principio de continuidad espacial para eliminar falsos positivos y correspondencias erróneas. Se han estudiado los efectos de la aplicación de dichos filtros, en etapas previas y posteriores al proceso de correspondencia, con eficiencia verificada favorablemente. Su aplicación ha permitido la obtención de un mayor número de correspondencias válidas en comparación con los resultados obtenidos sin la aplicación de los mismos, consiguiendo mejoras significativas en los mapas de disparidad y, por lo tanto, en los procesos globales de percepción y reconstrucción 3D.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

Dynamic virtual reality user interface for teleoperation of heterogeneous robot teams

This research investigates the possibility to improve current teleoperation control for heterogeneous robot teams using modern Human-Computer Interaction (HCI) techniques such as Virtual Reality. It proposes a dynamic teleoperation Virtual Reality User Interface (VRUI) framework to improve the current approach to teleoperating heterogeneous robot teams

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

The development of a human-robot interface for industrial collaborative system

Industrial robots have been identified as one of the most effective solutions for optimising output and quality within many industries. However, there are a number of manufacturing applications involving complex tasks and inconstant components which prohibit the use of fully automated solutions in the foreseeable future. A breakthrough in robotic technologies and changes in safety legislations have supported the creation of robots that coexist and assist humans in industrial applications. It has been broadly recognised that human-robot collaborative systems would be a realistic solution as an advanced production system with wide range of applications and high economic impact. This type of system can utilise the best of both worlds, where the robot can perform simple tasks that require high repeatability while the human performs tasks that require judgement and dexterity of the human hands. Robots in such system will operate as “intelligent assistants”. In a collaborative working environment, robot and human share the same working area, and interact with each other. This level of interface will require effective ways of communication and collaboration to avoid unwanted conflicts. This project aims to create a user interface for industrial collaborative robot system through integration of current robotic technologies. The robotic system is designed for seamless collaboration with a human in close proximity. The system is capable to communicate with the human via the exchange of gestures, as well as visual signal which operators can observe and comprehend at a glance. The main objective of this PhD is to develop a Human-Robot Interface (HRI) for communication with an industrial collaborative robot during collaboration in proximity. The system is developed in conjunction with a small scale collaborative robot system which has been integrated using off-the-shelf components. The system should be capable of receiving input from the human user via an intuitive method as well as indicating its status to the user ii effectively. The HRI will be developed using a combination of hardware integrations and software developments. The software and the control framework were developed in a way that is applicable to other industrial robots in the future. The developed gesture command system is demonstrated on a heavy duty industrial robot