Generator of the power supply system for a two-component sensor of angular speeds based on a dynamically tuned gyroscope

В статье рассматривается структурная схема и принцип работы задающего генератора системы питания двухкомпонентного датчика угловых скоростей на основе динамически настраиваемого гироскопа. Датчик является составной частью наземного прибора ориентации системы ориентации и навигации горнопроходческого комбайна. Предлагается вариант ее модернизации.In this the article deals with the block diagram and the operating principle of the generator of the power supply system of a two-component angular velocity sensor, based on a dynamically tuned gyroscope. The sensor is an integral part of the ground instrument for orienting the orientation and navigation system of the mining combine. A variant of its modernization is proposed

A review of sensor technology and sensor fusion methods for map-based localization of service robot

Service robot is currently gaining traction, particularly in hospitality, geriatric care and healthcare industries. The navigation of service robots requires high adaptability, flexibility and reliability. Hence, map-based navigation is suitable for service robot because of the ease in updating changes in environment and the flexibility in determining a new optimal path. For map-based navigation to be robust, an accurate and precise localization method is necessary. Localization problem can be defined as recognizing the robot’s own position in a given environment and is a crucial step in any navigational process. Major difficulties of localization include dynamic changes of the real world, uncertainties and limited sensor information. This paper presents a comparative review of sensor technology and sensor fusion methods suitable for map-based localization, focusing on service robot applications

Autonomous Flight in Unknown Indoor Environments

http://multi-science.metapress.com/content/80586kml376k2711/This paper presents our solution for enabling a quadrotor helicopter, equipped with a laser rangefinder sensor, to autonomously explore and map unstructured and unknown indoor environments. While these capabilities are already commodities on ground vehicles, air vehicles seeking the same performance face unique challenges. In this paper, we describe the difficulties in achieving fully autonomous helicopter flight, highlighting the differences between ground and helicopter robots that make it difficult to use algorithms that have been developed for ground robots. We then provide an overview of our solution to the key problems, including a multilevel sensing and control hierarchy, a high-speed laser scan-matching algorithm, an EKF for data fusion, a high-level SLAM implementation, and an exploration planner. Finally, we show experimental results demonstrating the helicopter's ability to navigate accurately and autonomously in unknown environments.National Science Foundation (U.S.) (NSF Division of Information and Intelligent Systems under grant # 0546467)United States. Army Research Office (ARO MAST CTA)Singapore. Armed Force

Curvature-Based Environment Description for Robot Navigation Using Laser Range Sensors

This work proposes a new feature detection and description approach for mobile robot navigation using 2D laser range sensors. The whole process consists of two main modules: a sensor data segmentation module and a feature detection and characterization module. The segmentation module is divided in two consecutive stages: First, the segmentation stage divides the laser scan into clusters of consecutive range readings using a distance-based criterion. Then, the second stage estimates the curvature function associated to each cluster and uses it to split it into a set of straight-line and curve segments. The curvature is calculated using a triangle-area representation where, contrary to previous approaches, the triangle side lengths at each range reading are adapted to the local variations of the laser scan, removing noise without missing relevant points. This representation remains unchanged in translation or rotation, and it is also robust against noise. Thus, it is able to provide the same segmentation results although the scene will be perceived from different viewpoints. Therefore, segmentation results are used to characterize the environment using line and curve segments, real and virtual corners and edges. Real scan data collected from different environments by using different platforms are used in the experiments in order to evaluate the proposed environment description algorithm

Digitalización del entorno a partir de un LIDAR HDL-64E

This paper proposes a map building system for an autonomous vehicle equipped with LIDAR technology, capable to obtain more than one million points per second. This paper proposes a Fast Local Map building Approach (LM) that it is use for autonomous local navigation, and construction of Global Map (GM) 2D and 3D for modeling the whole environment crossed by the vehicle. During the process of the global map building, we estimate the location of the vehicle with respect to its initial position.DOI: http://dx.doi.org/10.5377/nexo.v25i1.795 Nexo Revista Científica,Vol. 25, No. 01, pp.28-37/Junio 2012 En este trabajo se propone un sistema de reconstrucción de mapas para un vehículo autónomo equipado con tecnología LIDAR, capaz de obtener más de un millón de puntos por segundo. Dentro del artículo proponemos la construcción rápida de Mapas Locales (ML) 2D que nos servirán para la navegación local autónoma, y la construcción de Mapas Globales (MG) 2D y 3D que modelizán el ambiente recorrido por el vehículo. Durante el proceso de construcción del Mapa Global se calcula la localización del vehículo con respecto a su posición inicial.DOI: http://dx.doi.org/10.5377/nexo.v25i1.795 Nexo Revista Científica,Vol. 25, No. 01, pp.28-37/Junio 2012

Digitalización del entorno a partir de un LIDAR HDL-64E

This paper proposes a map building system for an autonomous vehicle equipped with LIDAR technology, capable to obtain more than one million points per second. This paper proposes a Fast Local Map building Approach (LM) that it is use for autonomous local navigation, and construction of Global Map (GM) 2D and 3D for modeling the whole environment crossed by the vehicle. During the process of the global map building, we estimate the location of the vehicle with respect to its initial position.Keywords: 2D map building, 3D map building, localization.En este trabajo se propone un sistema de reconstrucción de mapas para un vehículo autónomo equipado con tecnología LIDAR, capaz de obtener más de un millón de puntos por segundo. Dentro del artículo proponemos la construcción rápida de Mapas Locales (ML) 2D que nos servirán para la navegación local autónoma, y la construcción de Mapas Globales (MG) 2D y 3D que modelizán el ambiente recorrido por el vehículo. Durante el proceso de construcción del Mapa Global se calcula la localización del vehículo con respecto a su posición inicial.Palabras claves: Construcción de mapas 2D, construcción de mapas 3D, localización

Validación de máquina briqueteadora para el aprovechamiento de la cascarilla de café como combustible

La investigación contó con el apoyo técnico y financiero de la Fundación para el Desarrollo Tecnológico Agropecuario y Forestal de Nicaragua (FUNICA) y su finalidad fue validar una máquina briqueteadora de tornillo helicoidal para el aprovechamiento de la cascarilla de café como combustible. Se determinaron las propiedades de la cascarilla de café, se caracterizaron las briquetas elaboradas con la máquina briqueteadora, comparándolas con las elaboradas artesanalmente, asimismo se establecieron las ventajas económicas de dicho equipo, y  posteriormente se realizó un análisis comparativo entre las briquetas y la leña como combustible. Para elaborar estos análisis se ejecutaron varias actividades entre ellas: pruebas de ceniza, humedad, granulometría, análisis del funcionamiento del equipo, desarrollo de producto densificado (briquetas) con diferentes aglutinantes, pruebas de dióxido de carbono, poder calórico, y se realizó el cálculo de la inversión inicial, costos de producción de las briquetas. Las pruebas realizadas dieron como resultado que entre menor sea el tamaño de las partículas de la materia prima (cascarilla) se obtiene mayor calidad del producto densificado, sin embargo la máquina de tornillo helicoidal, resultó ser un equipo no funcional, debido al sistema de compactación que presentaba. Por éste y otros inconvenientes se descartó, por lo tanto se recurrió a dos prototipos de maquinaria como son el Molde de madera y la Prensa manual, este último presenta un sistema de compactación que permite obtener un producto de calidad al usar una mezcla de almidón cocido con cascarilla triturada. Con esto se procedió a realizar los cálculos de producción obteniendo que estos son mayores en la prensa, debido a su nivel de producción, en cambio en el molde son menores, pero su producto no es suficientemente compacto. Dentro del análisis comparativo entre la leña y la briqueta se encontró que ésta última presenta mayor poder calórico, genera menos dióxido de carbono, aspecto que podemos destacar desde el punto de vista ambiental

2D LIDAR Aided INS for vehicle positioning in urban environments

This paper presents a novel method to utilize\textit{2D} LIDAR for INS (Inertial Navigation System) aiding to improve\textit{3D} vehicle position estimation accuracy, especially when GNSS signals are shadowed.In the proposed framework, 2D LIDAR aiding is carried out without imposing any assumptions on the vehicle motion (e.g. we allow full six degree-of freedom motion).To achieve this, a closed-form formula is derived to predict the line measurement in the LIDAR's frame.This makes the feature association, residual formation and GUI display possible.With this formula, the Extended Kalman Filter (EKF) can be employed in a straightforward manner to fuse the LIDAR and IMU data to estimate the full state of the vehicle.Preliminary experimental results show the effectiveness of the LIDAR aiding in reducing the state estimation uncertainty along certain directions, when GNSS signals are shadowed

INS/GPS/LiDAR integrated navigation system for urban and indoor environments using hybrid scan matching algorithm

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory

Correspondenceless scan-to-map-scan matching of homoriented 2D scans for mobile robot localisation

The objective of this study is improving the location estimate of a mobile robot capable of motion on a plane and mounted with a conventional 2D LIDAR sensor, given an initial guess for its location on a 2D map of its surroundings. Documented herein is the theoretical reasoning behind solving a matching problem between two homoriented 2D scans, one derived from the robot's physical sensor and one derived by simulating its operation within the map, in a manner that does not require the establishing of correspondences between their constituting rays. Two results are proved and subsequently shown through experiments. The first is that the true position of the sensor can be recovered with arbitrary precision when the physical sensor reports faultless measurements and there is no discrepancy between the environment the robot operates in and its perception of it by the robot. The second is that when either is affected by disturbance, the location estimate is bound in a neighbourhood of the true location whose radius is proportional to the affecting disturbance.Comment: 19 pages, 19 figure