Developing a person guidance module for hospital robots

This dissertation describes the design and implementation of the Person Guidance Module (PGM) that enables the IWARD (Intelligent Robot Swarm for attendance, Recognition, Cleaning and delivery) base robot to offer route guidance service to the patients or visitors inside the hospital arena. One of the common problems encountered in huge hospital buildings today is foreigners not being able to find their way around in the hospital. Although there are a variety of guide robots currently existing on the market and offering a wide range of guidance and related activities, they do not fit into the modular concept of the IWARD project. The PGM features a robust and foolproof non-hierarchical sensor fusion approach of an active RFID, stereovision and cricket mote sensor for guiding a patient to the X-ray room, or a visitor to a patient’s ward in every possible scenario in a complex, dynamic and crowded hospital environment. Moreover, the speed of the robot can be adjusted automatically according to the pace of the follower for physical comfort using this system. Furthermore, the module performs these tasks in any unconstructed environment solely from a robot’s onboard perceptual resources in order to limit the hardware installation costs and therefore the indoor setting support. Similar comprehensive solution in one single platform has remained elusive in existing literature. The finished module can be connected to any IWARD base robot using quick-change mechanical connections and standard electrical connections. The PGM module box is equipped with a Gumstix embedded computer for all module computing which is powered up automatically once the module box is inserted into the robot. In line with the general software architecture of the IWARD project, all software modules are developed as Orca2 components and cross-complied for Gumstix’s XScale processor. To support standardized communication between different software components, Internet Communications Engine (Ice) has been used as middleware. Additionally, plug-and-play capabilities have been developed and incorporated so that swarm system is aware at all times of which robot is equipped with PGM. Finally, in several field trials in hospital environments, the person guidance module has shown its suitability for a challenging real-world application as well as the necessary user acceptance

Un nuevo concepto en escáner adaptativo de bajo costo para robots móviles

El problema fundamental en las aplicaciones de robots móviles, es la necesidad de conocer con exactitud la posición del vehículo, para poder localizarse en el espacio y evitar obstáculos en su camino. En la búsqueda de una solución, los investigadores e ingenieros han desarrollado diferentes sensores, sistemas y técnicas.Los robots móviles modernos se basan en la información obtenida de diferentes sensores y en sofisticados algoritmos de fusión de datos. Por tal razón, en este artículo se propone un nuevo concepto de escáner de adaptación a bajo costo, basándose en patrones de luz proyectados. La ventaja principal del sistema propuesto es: su adaptabilidad, que permite en los robots el escaneo rápido de los alrededores durante la búsqueda de obstáculos y una exploración más detallada de un objeto determinado, para poder recu-perar así, su configuración de la superficie y realizar algunos análisis limitados.El artículo aborda el concepto de un escáner de este tipo, donde se logró la prueba del concepto utilizando un proyector de oficina DLP. Durante las mediciones, la exactitud del sistema propuesto se puso a prueba, usando obstáculos con objetos de configuraciones conocidas. De esta manera, los resultados obtenidos son presentados, analizados y se discuten las conclusiones sobre el desempeño del sistema para generar posibles mejoramientos.A fundamental problem in mobile robot applications is the need for accurate knowledge of the position of a vehicle for localizing itself and for avoiding obstacles in its path. In the search for a solution to this problem, researchers and engineers have developed different sensors, systems and techniques. Modern mobile robots relay information obtained from a variety of sensors and sophisticated data fusion algorithms. In this paper, a novel concept for a low-cost adaptive scanner based on a projected light pattern is proposed. The main advantage of the proposed system is its adaptivity, which enables the rapid scanning of the robot’s surroundings in search of obstacles and a more detailed scan of a single object to retrieve its surface configuration and perform some limited analyses. This paper addresses the concept behind such a scanner, where a proof-of-concept is achieved using an office DLP projector. During the measurements, the accuracy of the proposed system was tested on obstacles and objects with known configurations. The obtained results are presented and analyzed, and conclusions about the system’s performance and possible improvements are discussed

THINK Robots

Retailers rely on Kiva Systems’ warehouse robots to deliver order-fulfillment services, but current systems are frequently interrupted and require physical barriers to ensure compliance with safety regulations since Kiva does not currently rely on the obstacle detection system to contribute to the functional safety of its overall system. After evaluating operating scenarios and detection technologies, a solution comprised of a stereo vision system to detect static objects and a radio ranging system to identify humans in the vicinity was designed, built, and verified, with the aim of reducing undue downtime and allowing humans and robots to safely interact without physical restrictions

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

GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

3D position tracking for all-terrain robots

Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. Such robots find their application in scientific exploration of hostile environments like deserts, volcanoes, in the Antarctic or on other planets. They are also of high interest for search and rescue operations after natural or artificial disasters. The challenges to bring autonomy to all terrain rovers are wide. In particular, it requires the development of systems capable of reliably navigate with only partial information of the environment, with limited perception and locomotion capabilities. Amongst all the required functionalities, locomotion and position tracking are among the most critical. Indeed, the robot is not able to fulfill its task if an inappropriate locomotion concept and control is used, and global path planning fails if the rover loses track of its position. This thesis addresses both aspects, a) efficient locomotion and b) position tracking in rough terrain. The Autonomous System Lab developed an off-road rover (Shrimp) showing excellent climbing capabilities and surpassing most of the existing similar designs. Such an exceptional climbing performance enables an extension in the range of possible areas a robot could explore. In order to further improve the climbing capabilities and the locomotion efficiency, a control method minimizing wheel slip has been developed in this thesis. Unlike other control strategies, the proposed method does not require the use of soil models. Independence from these models is very significant because the ability to operate on different types of soils is the main requirement for exploration missions. Moreover, our approach can be adapted to any kind of wheeled rover and the processing power needed remains relatively low, which makes online computation feasible. In rough terrain, the problem of tracking the robot's position is tedious because of the excessive variation of the ground. Further, the field of view can vary significantly between two data acquisition cycles. In this thesis, a method for probabilistically combining different types of sensors to produce a robust motion estimation for an all-terrain rover is presented. The proposed sensor fusion scheme is flexible in that it can easily accommodate any number of sensors, of any kind. In order to test the algorithm, we have chosen to use the following sensory inputs for the experiments: 3D-Odometry, inertial measurement unit (accelerometers, gyros) and visual odometry. The 3D-Odometry has been specially developed in the framework of this research. Because it accounts for ground slope discontinuities and the rover kinematics, this technique results in a reasonably precise 3D motion estimate in rough terrain. The experiments provided excellent results and proved that the use of complementary sensors increases the robustness and accuracy of the pose estimate. In particular, this work distinguishes itself from other similar research projects in the following ways: the sensor fusion is performed with more than two sensor types and sensor fusion is applied a) in rough terrain and b) to track the real 3D pose of the rover. Another result of this work is the design of a high-performance platform for conducting further research. In particular, the rover is equipped with two computers, a stereovision module, an omnidirectional vision system, an inertial measurement unit, numerous sensors and actuators and electronics for power management. Further, a set of powerful tools has been developed to speed up the process of debugging algorithms and analyzing data stored during the experiments. Finally, the modularity and portability of the system enables easy adaptation of new actuators and sensors. All these characteristics speed up the research in this field

Advances in Stereo Vision

Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints

A coordinated UAV deployment based on stereovision reconnaissance for low risk water assessment

Biologists and management authorities such as the World Health Organisation require monitoring of water pollution for adequate management of aquatic ecosystems. Current water sampling techniques based on human samplers are time consuming, slow and restrictive. This thesis takes advantage of the recent affordability and higher flexibility of Unmanned Aerial Vehicles (UAVs) to provide innovative solutions to the problem. The proposed solution involves having one UAV, “the leader”, equipped with sensors that are capable of accurately estimating the wave height in an aquatic environment, if the region identified by the leader is characterised as having a low wave height, the area is deemed suitable for landing. A second UAV, “the follower UAV”, equipped with a payload such as an Autonomous Underwater Vehicle (AUV) can proceed to the location identified by the leader, land and deploy the AUV into the water body for the purposes of water sampling. The thesis acknowledges there are two main challenges to overcome in order to develop the proposed framework. Firstly, developing a sensor to accurately measure the height of a wave and secondly, achieving cooperative control of two UAVs. Two identical cameras utilising a stereovision approach were developed for capturing three-dimensional information of the wave distribution in a non-invasive manner. As with most innovations, laboratory based testing was necessary before a full-scale implementation can be attempted. Preliminary results indicate that provided a suitable stereo matching algorithm is applied, one can generate a dense 3D reconstruction of the surface to allow estimation of the wave height parameters. Stereo measurements show good agreement with the results obtained from a wave probe in both the time and frequency domain. The mean absolute error for the average wave height and the significant wave height is less than 1cm from the acquired time series data set. A formation-flying algorithm was developed to allow cooperative control between two UAVs. Results show that the follower was able to successfully track the leader’s trajectory and in addition maintain the given separation distance from the leader to within 1m tolerance through the course of the experiments despite windy conditions, low sampling rate and poor accuracy of the GPS sensors. In the closing section of the thesis, near real-time dense 3D reconstruction and wave height estimation from the reconstructed 3D points is demonstrated for an aquatic body using the leader UAV. Results show that for a pair of images taken at a resolution of 320 by 240 pixels up to 21,000 3D points can be generated to provide a dense 3D reconstruction of the water surface within the field of view of the cameras