3DMADMAC|AUTOMATED: synergistic hardware and software solution for automated 3D digitization of cultural heritage objects

In this article a fully automated 3D shape measurement system and data processing algorithms are presented. Main purpose of this system is to automatically (without any user intervention) and rapidly (at least ten times faster than manual measurement) digitize whole object’s surface with some limitations to its properties: maximum measurement volume is described as a cylinder with 2,8m height and 0,6m radius, maximum object's weight is 2 tons.  Measurement head is automatically calibrated by the system for chosen working volume (from 120mm x 80mm x 60mm and ends up to 1,2m x 0,8m x 0,6m). Positioning of measurement head in relation to measured object is realized by computer-controlled manipulator. The system is equipped with two independent collision detection modules to prevent damaging measured object with moving sensor’s head. Measurement process is divided into three steps. First step is used for locating any part of object’s surface in assumed measurement volume. Second step is related to calculation of "next best view" position of measurement head on the base of existing 3D scans. Finally small holes in measured 3D surface are detected and measured. All 3D data processing (filtering, ICP based fitting and final views integration) is performed automatically. Final 3D model is created on the base of user specified parameters like accuracy of surface representation and/or density of surface sampling. In the last section of the paper, exemplary measurement result of two objects: biscuit (from the collection of Museum Palace at Wilanów) and Roman votive altar (Lower Moesia, II-III AD) are presented

Distance and Cable Length Measurement System

A simple, economic and successful design for distance and cable length detection is presented. The measurement system is based on the continuous repetition of a pulse that endlessly travels along the distance to be detected. There is a pulse repeater at both ends of the distance or cable to be measured. The endless repetition of the pulse generates a frequency that varies almost inversely with the distance to be measured. The resolution and distance or cable length range could be adjusted by varying the repetition time delay introduced at both ends and the measurement time. With this design a distance can be measured with centimeter resolution using electronic system with microsecond resolution, simplifying classical time of flight designs which require electronics with picosecond resolution. This design was also applied to position measurement

Omnidirectional Vision-based Robot Localization on Soccer Field by Particle Filter

[[abstract]]An omnidirectional vision-based localization method based on the particle Alter is proposed to achieve the location of robot on a soccer field in this paper. Two kinds of sensor information are considered in the method to let the robot on the soccer field can estimate its location and then to decide an appropriate strategy. One is the robot action sensor information obtained by the motor's feedback and the other is the observation sensor information obtained by the image captured by an omnidirectional vision system. The action sensor information is used to expect the robot location distribution. The location distribution is represented by particles. The omnidirectional image is used to observe the environment information. The differences between these particles location's environment information and the robot observation environment information are considered to calculate the belief values of particles. Then the posture of the particle with the highest belief is used to be the estimated posture of the robot. Some experimental results are presented to illustrate the effectiveness of the proposed method.[[conferencetype]]國際[[conferencedate]]20100818~20100821[[iscallforpapers]]Y[[conferencelocation]]Taipei, Taiwa

SISTEMA DE LOCALIZACIÓN POR RADAR PARA UN ROBOT DE CONFIGURACIÓN ACKERMANN (RADAR LOCATION SYSTEM FOR AN ACKERMANN CONFIGURATION ROBOT)

Resumen El proyecto consiste en desarrollar un sistema de localización capaz de llevar a cabo el control de la trayectoria de un robot móvil, este robot está diseñado bajo los parámetros de la configuración de movimiento Ackermann y fue construido con un chasis de acrílico de 3 mm en el que se montaron los componentes que lo conforman, los cuales son: el sistema de dirección, sistema de tracción y el sistema de control. Además, se recurrió a la tecnología de impresión 3D para fabricar una base necesaria para evitar interferencias en el escáner láser. Para la elaboración del sistema de localización se requiere el uso del escáner láser RPLiDAR modelo A1M8, que actúa como el principal componente para obtener una retroalimentación del ambiente. Esto se traduce como el uso de los datos que entrega el escáner, los cuales mediante análisis matemáticos ayudan al establecimiento de un sistema coordenado y el cálculo de la posición. La conexión del sistema de localización y el sistema de control brinda la posibilidad de programar las trayectorias a seguir por el robot, sin embargo, debido a la existencia de errores se implementa un sistema de recálculo de trayectoria que toma como principales herramientas de funcionamiento la cinemática del robot y el filtro de partículas creado para el cálculo de incertidumbre. Este recálculo reduce considerablemente el error en la trayectoria, lo cual queda demostrado en las pruebas realizadas en una trayectoria compuesta por: 3 movimientos rectos de 40 cm de longitud y 2 movimientos curvos con un radio de curvatura de 40 cm. La precisión en cuanto al cumplimiento de la trayectoria del sistema de recálculo es alta, ya que se observan variaciones por debajo de los 10 cm, comparado con un comportamiento ideal. Palabras clave: configuración Ackermann, escáner láser, robot móvil, incertidumbre, sistemas de radar, cinemática, filtro de partículas. Abstract The project consists of developing a location system capable of controlling the trajectory of a mobile robot, this robot is designed under the parameters of the Ackermann movement configuration and was built with a 3 mm acrylic chassis in the that the components that comprise it were assembled, which are: the steering system, traction system and the control system; In addition, 3D printing technology was used to manufacture a necessary base to avoid interference in the laser scanner. For the development of the location system, the use of the RPLiDAR model A1M8 laser scanner is required, which acts as the main component to obtain feedback from the environment in which the robot moves, this is translated as the use of the data provided by the scanner, which through mathematical analysis help the establishment of a coordinate system and the calculation of the position. The connection of the location system and the control system offers the possibility of programming the trajectories to be followed by the robot, however, due to the existence of errors, a trajectory recalculation system is implemented that takes the kinematics as its main operating tools. of the robot and the particle filter created for the uncertainty calculation; This recalculation considerably reduces the error in the trajectory, which is demonstrated in the tests carried out on a trajectory composed of 3 straight movements of 40 cm in length and 2 curved movements with a radius of curvature of 40 cm. The precision in terms of compliance with the trajectory of the recalculation system is high, since variations are observed below 10 cm compared to an ideal behavior. Keywords: Ackermann configuration, laser scanner, mobile robot, uncertainty, radar systems, kinematics, particle filter

Towards Natural Human Control and Navigation of Autonomous Wheelchairs

Approximately 2.2 million people in the United States depend on a wheelchair to assist with their mobility. Often times, the wheelchair user can maneuver around using a conventional joystick. Visually impaired or wheelchair patients with restricted hand mobility, such as stroke, arthritis, limb injury, Parkinson’s, cerebral palsy or multiple sclerosis, prevent them from using traditional joystick controls. The resulting mobility limitations force these patients to rely on caretakers to perform everyday tasks. This minimizes the independence of the wheelchair user. Modern day speech recognition systems can be used to enhance user experiences when using electronic devices. By expanding the motorized wheelchair control interface to include the detection of user speech commands, the independence is given back to the mobility impaired. A speech recognition interface was developed for a smart wheelchair. By integrating navigation commands with a map of the wheelchair’s surroundings, the wheelchair interface is more natural and intuitive to use. Complex speech patterns are interpreted for users to command the smart wheelchair to navigate to specified locations within the map. Pocketsphinx, a speech toolkit, is used to interpret the vocal commands. A language model and dictionary were generated based on a set of possible commands and locations supplied to the speech recognition interface. The commands fall under the categories of speed, directional, or destination commands. Speed commands modify the relative speed of the wheelchair. Directional commands modify the relative direction of the wheelchair. Destination commands require a known location on a map to navigate to. The completion of the speech input processer and the connection between wheelchair components via the Robot Operating System make map navigation possible

RGB-D Scan Matching basado en Covariance Matrix Adaptation - Evolution Strategy

En el campo de la robótica, la búsqueda de algoritmos y métodos que permitan crear mapas robustos es uno de los temas más estudiados en los últimos años. Cada vez es mayor el interés en desarrollar robots autónomos, con el fin de emplearlos para tareas difíciles o que no pueden ser realizadas por los humanos, como por ejemplo exploraciones espaciales u operaciones de rescate. Para ello, es necesario que el robot sea capaz de enfrentarse a un entorno desconocido, y localizarse dentro de él. Así surge el problema del SLAM (Simultaneous Localization and Mapping), que consiste en que el robot sea capaz de ir construyendo un mapa de un entorno desconocido, y a la vez ubicarse dentro de él. Un aspecto muy ligado a este problema es el scan matching, objeto principal de este trabajo. Con el scan matching se busca encontrar la transformación rígida (traslación y rotación) que alinea dos barridos del entorno diferentes. Estos barridos son proporcionados por sensores como cámaras RGB. A lo largo de los años, se han ido buscando nuevas técnicas con las que poder realizar el matching. Algunas de estas técnicas son las denominadas Estrategias Evolutivas, mediante las que se busca resolver problemas de optimización basándose en los procesos de la evolución natural. En estas técnicas, se tiene una población inicial que evoluciona y varía de acuerdo al valor de coste obtenido hasta que converge a una solución. En este trabajo se ha implementado una solución al scan matching basada en el Covariance Matrix Adaptation-Evolution Strategy. Con este método se busca realizar el matching entre dos scans minimizando una función de coste. Además se utilizan las propiedades del color para seleccionar los puntos característicos de cada barrido, reduciéndose el coste computacional del método.In the robotics field, the research of new algorithms and methods that allow creating robust maps is one of the most studied issues during the last years. Interest in developing autonomous robots is growing further, in order to use them for difficult tasks or other tasks that can not be done by humans, as for example space explorations or rescue operations. To do that, it is necessary that the robot has the capacity of dealing with an unknown environment and of being located itself in the map. For that matter SLAM problem appears (Simultaneous Localization and Mapping), which consists of the fact that the robot is capable of building a map of an unknown environment, and simultaneously of locating itself inside this environment. A highly related aspect to this problem is scan matching, which is the main subject of this project. Scan matching’s purpose is finding the rigid transformation (translation and rotation) that aligns two different scans of the environment. These scans are provided by sensors such as RGB cameras. Throughout the years, researchers have been looking for new techniques that could perform the matching. Some of these methods are the so called Evolutionary Strategies, by means of which it is look to solve optimization problems based on the process of natural evolution. In these techniques, there is an initial population that evolves and changes according to the cost value obtained until it converges to a solution. In this work, a solution of the Scan Matching problem has been implemented based on the Covariance Matrix Adaptation-Evolution Strategy algorithm. With this method it is look to achieve the matching between two scans by minimizing a cost function. Color properties are also used to select featured points in the scans, reducing the computational cost of the method.Ingeniería en Tecnologías Industriale

Estudo e desenvolvimento de um sistema de autolocalização para um veículo autónomo

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e ComputadoresO desenvolvimento de sistemas de localização robustos, eficientes e de baixo custo permanece como uma das questões importantes dos veículos autónomos. Esta dissertação foi desenvolvida em parceria com o CEiiA e tem como principal objetivo o desenvolvimento de um sistema de autolocalização de baixo custo para um veículo autónomo que circulará no exterior. O cumprimento deste objetivo envolveu a especificação, implementação e teste de um protótipo. Envolveu também o desenvolvimento do firmware do microcontrolador (C/C++) para realizar a recolha e comunicação dos dados recolhidos pelos diversos sensores. A plataforma móvel utilizada para testes foi uma bicicleta na qual se integraram um módulo GPS, um encoder absoluto, um alternador (utilizado como um encoder incremental), um giroscópio, um acelerómetro e um magnetómetro. Os dados são adquiridos a uma frequência de 40 Hz e guardados num cartão μSD ou transmitidos através de um módulo de comunicação sem fios XBee. Para realizar a fusão sensorial exploraram-se o filtro complementar, o filtro de Kalman Extended e o filtro de Kalman Unscented, através do software Matlab. De forma a permitir a visualização dos resultados, desenvolveu-se uma interface gráfica em HTML, CSS e Javascript. Realizaram-se diversos testes ao sistema, tendo-se obtido na medição da posição do veículo um erro máximo de 10 m por parte do GPS. Foi também verificado que o erro da odometria é proporcional ao aumento da complexidade da trajetória e da distância percorrida. De entre os três filtros aplicados, o filtro complementar revelou ser uma solução satisfatória para percursos simples. Não houve diferenças significativas entre os resultados obtidos com os diferentes filtros de Kalman.The development of robust, efficient and low-cost localization systems remains one of the important issues of autonomous vehicles. This dissertation was developed in partnership with CEiiA and its main objective is the development of a low-cost self-localization system for an autonomous vehicle that will circulate in a non-controlled environment. The fulfillment of this objective involved the specification, implementation and testing of a prototype. It also involved the development of microcontroller firmware (C/C++) to gather and communicate the data collected by the various sensors. The mobile platform used for testing was a bicycle in which a GPS module, an absolute encoder, an alternator (used as an incremental encoder), a gyroscope, an accelerometer and a magnetometer were integrated. The data is acquired at a frequency of 40Hz and stored on a μSD card or transmitted through an XBee wireless communication module. The Complementary filter, the Extended Kalman filter and the Unscented Kalman filter were explored through Matlab software. In order to allow the visualization of the results, a graphical user interface was developed in HTML, CSS and Javascript. Several tests were performed on the system, and a maximum error of 10 m was obtained by the GPS in the vehicle position measurement. It was also verified that the error of the odometry is proportional to the increase of the complexity and distance covered. Of the three filters applied, the complimentary filter proved to be a satisfactory solution for simple routes. There was no significant differences between the results obtained with the different Kalman filters

Unidade de processamento e sistema de visão para um robô humanóide

Mestrado em Engenharia Electrónica e TelecomunicaçõesEste trabalho descreve a integração da Unidade Central de Processamento, um computador embebido, numa plataforma humanóide e o desenvolvimento do sistema de visão do robô. É abordado o processo de alteração da estrutura da plataforma para a integração física, e também a configuração e implementação do ambiente de desenvolvimento por forma a permitir a integra ção numa arquitectura de controlo distribuída já existente. O sistema de visão é baseado numa unidade pan-tilt que movimenta uma câmara para aquisição de imagem. A informação retirada da imagem adquirida é processada e usada para fazer o seguimento de um objecto. Para o seguimento são usados dois algoritmos de controlo baseados na imagem. ABSTRACT: This report describes the integration of the Central Control Unit, an embedded computer, on an humanoid platform and the development of the robot's vision system. The necessary changes on the physical support are shown as well as the configuration and implementation of the development environment, in order to allow the integration with the existing distributed architecture. The vision system is based on a pan and tilt unit supporting a color CCD camera for image aquisition. The visual tracking is based on the features of the acquired and processed image. Two diferent image-based algorithms are used for control

Omnidirectional vision scan matching for robot localization in dynamic environments

The localization problem for an autonomous robot moving in a known environment is a well-studied problem which has seen many elegant solutions. Robot localization in a dynamic environment populated by several moving obstacles, however, is still a challenge for research. In this paper, we use an omnidirectional camera mounted on a mobile robot to perform a sort of scan matching. The omnidirectional vision system finds the distances of the closest color transitions in the environment, mimicking the way laser rangefinders detect the closest obstacles. The similarity of our sensor with classical rangefinders allows the use of practically unmodified Monte Carlo algorithms, with the additional advantage of being able to easily detect occlusions caused by moving obstacles. The proposed system was initially implemented in the RoboCup Middle-Size domain, but the experiments we present in this paper prove it to be valid in a general indoor environment with natural color transitions. We present localization experiments both in the RoboCup environment and in an unmodified office environment. In addition, we assessed the robustness of the system to sensor occlusions caused by other moving robots. The localization system runs in real-time on low-cost hardware