Mapping and Semantic Perception for Service Robotics

Para realizar una tarea, los robots deben ser capaces de ubicarse en el entorno. Si un robot no sabe dónde se encuentra, es imposible que sea capaz de desplazarse para alcanzar el objetivo de su tarea. La localización y construcción de mapas simultánea, llamado SLAM, es un problema estudiado en la literatura que ofrece una solución a este problema. El objetivo de esta tesis es desarrollar técnicas que permitan a un robot comprender el entorno mediante la incorporación de información semántica. Esta información también proporcionará una mejora en la localización y navegación de las plataformas robóticas. Además, también demostramos cómo un robot con capacidades limitadas puede construir de forma fiable y eficiente los mapas semánticos necesarios para realizar sus tareas cotidianas.El sistema de construcción de mapas presentado tiene las siguientes características: En el lado de la construcción de mapas proponemos la externalización de cálculos costosos a un servidor en nube. Además, proponemos métodos para registrar información semántica relevante con respecto a los mapas geométricos estimados. En cuanto a la reutilización de los mapas construidos, proponemos un método que combina la construcción de mapas con la navegación de un robot para explorar mejor un entorno y disponer de un mapa semántico con los objetos relevantes para una misión determinada.En primer lugar, desarrollamos un algoritmo semántico de SLAM visual que se fusiona los puntos estimados en el mapa, carentes de sentido, con objetos conocidos. Utilizamos un sistema monocular de SLAM basado en un EKF (Filtro Extendido de Kalman) centrado principalmente en la construcción de mapas geométricos compuestos únicamente por puntos o bordes; pero sin ningún significado o contenido semántico asociado. El mapa no anotado se construye utilizando sólo la información extraída de una secuencia de imágenes monoculares. La parte semántica o anotada del mapa -los objetos- se estiman utilizando la información de la secuencia de imágenes y los modelos de objetos precalculados. Como segundo paso, mejoramos el método de SLAM presentado anteriormente mediante el diseño y la implementación de un método distribuido. La optimización de mapas y el almacenamiento se realiza como un servicio en la nube, mientras que el cliente con poca necesidad de computo, se ejecuta en un equipo local ubicado en el robot y realiza el cálculo de la trayectoria de la cámara. Los ordenadores con los que está equipado el robot se liberan de la mayor parte de los cálculos y el único requisito adicional es una conexión a Internet.El siguiente paso es explotar la información semántica que somos capaces de generar para ver cómo mejorar la navegación de un robot. La contribución en esta tesis se centra en la detección 3D y en el diseño e implementación de un sistema de construcción de mapas semántico.A continuación, diseñamos e implementamos un sistema de SLAM visual capaz de funcionar con robustez en entornos poblados debido a que los robots de servicio trabajan en espacios compartidos con personas. El sistema presentado es capaz de enmascarar las zonas de imagen ocupadas por las personas, lo que aumenta la robustez, la reubicación, la precisión y la reutilización del mapa geométrico. Además, calcula la trayectoria completa de cada persona detectada con respecto al mapa global de la escena, independientemente de la ubicación de la cámara cuando la persona fue detectada.Por último, centramos nuestra investigación en aplicaciones de rescate y seguridad. Desplegamos un equipo de robots en entornos que plantean múltiples retos que implican la planificación de tareas, la planificación del movimiento, la localización y construcción de mapas, la navegación segura, la coordinación y las comunicaciones entre todos los robots. La arquitectura propuesta integra todas las funcionalidades mencionadas, asi como varios aspectos de investigación novedosos para lograr una exploración real, como son: localización basada en características semánticas-topológicas, planificación de despliegue en términos de las características semánticas aprendidas y reconocidas, y construcción de mapas.In order to perform a task, robots need to be able to locate themselves in the environment. If a robot does not know where it is, it is impossible for it to move, reach its goal and complete the task. Simultaneous Localization and Mapping, known as SLAM, is a problem extensively studied in the literature for enabling robots to locate themselves in unknown environments. The goal of this thesis is to develop and describe techniques to allow a service robot to understand the environment by incorporating semantic information. This information will also provide an improvement in the localization and navigation of robotic platforms. In addition, we also demonstrate how a simple robot can reliably and efficiently build the semantic maps needed to perform its quotidian tasks. The mapping system as built has the following features. On the map building side we propose the externalization of expensive computations to a cloud server. Additionally, we propose methods to register relevant semantic information with respect to the estimated geometrical maps. Regarding the reuse of the maps built, we propose a method that combines map building with robot navigation to better explore a room in order to obtain a semantic map with the relevant objects for a given mission. Firstly, we develop a semantic Visual SLAM algorithm that merges traditional with known objects in the estimated map. We use a monocular EKF (Extended Kalman Filter) SLAM system that has mainly been focused on producing geometric maps composed simply of points or edges but without any associated meaning or semantic content. The non-annotated map is built using only the information extracted from an image sequence. The semantic or annotated parts of the map –the objects– are estimated using the information in the image sequence and the precomputed object models. As a second step we improve the EKF SLAM presented previously by designing and implementing a visual SLAM system based on a distributed framework. The expensive map optimization and storage is allocated as a service in the Cloud, while a light camera tracking client runs on a local computer. The robot’s onboard computers are freed from most of the computation, the only extra requirement being an internet connection. The next step is to exploit the semantic information that we are able to generate to see how to improve the navigation of a robot. The contribution of this thesis is focused on 3D sensing which we use to design and implement a semantic mapping system. We then design and implement a visual SLAM system able to perform robustly in populated environments due to service robots work in environments where people are present. The system is able to mask the image regions occupied by people out of the rigid SLAM pipeline, which boosts the robustness, the relocation, the accuracy and the reusability of the geometrical map. In addition, it estimates the full trajectory of each detected person with respect to the scene global map, irrespective of the location of the moving camera at the point when the people were imaged. Finally, we focus our research on rescue and security applications. The deployment of a multirobot team in confined environments poses multiple challenges that involve task planning, motion planning, localization and mapping, safe navigation, coordination and communications among all the robots. The architecture integrates, jointly with all the above-mentioned functionalities, several novel features to achieve real exploration: localization based on semantic-topological features, deployment planning in terms of the semantic features learned and recognized, and map building.<br /

Design definition of the Laser Atmospheric Wind Sounder (LAWS), phase 2. Volume 2: Final report

Lockheed personnel, along with team member subcontractors and consultants, have performed a preliminary design for the LAWS Instrument. Breadboarding and testing of a LAWS class laser have also been performed. These efforts have demonstrated that LAWS is a feasible Instrument and can be developed with existing state-of-the-art technology. Only a commitment to fund the instrument development and deployment is required to place LAWS in orbit and obtain the anticipated science and operational forecasting benefits. The LAWS Science Team was selected in 1988-89 as were the competing LAWS phase 1/2 contractor teams. The LAWS Science Team developed requirements for the LAWS Instrument, and the NASA/LAWS project office defined launch vehicle and platform design constraints. From these requirements and constraints, the lockheed team developed LAWS Instrument concepts and configurations. A system designed to meet these requirements and constraints is outlined. The LAWS primary subsystem and interfaces - laser, optical, and receiver/processor - required to assemble a lidar are identified. Also identified are the support subsystems required for the lidar to function from space: structures and mechanical, thermal, electrical, and command and data management. The Lockheed team has developed a preliminary design of a LAWS Instrument System consisting of these subsystems and interfaces which will meet the requirements and objectives of the Science Team. This final report provides a summary of the systems engineering analyses and trades of the LAWS. Summaries of the configuration, preliminary designs of the subsystems, testing recommendations, and performance analysis are presented. Environmental considerations associated with deployment of LAWS are discussed. Finally, the successful LAWS laser breadboard effort is discussed along with the requirements and test results

Understanding How Agricultural Intensification Impacts Ring-Necked Pheasant Distribution and Survival in Eastern South Dakota

Historically, pheasants (Phasianus colchicus) have thrived in South Dakota in conjunction with successful land retirement programs or early farming practices through the 1950s, which created interspersions of agriculture and native landscapes that were ideal for pheasants. Recently, the Prairie Pothole ecosystem has undergone rapid agroeconomic expansion, effectively reducing ideal interspersions of native prairie and cropland into agriculturally homogeneous landscapes. Indices of pheasant abundance have suggested persistent population declines since 2008, raising concerns regarding landscape suitability. Our goal was to understand how agriculture intensification impacts pheasant ecology. The objectives were to: 1) estimate overwinter hen probability of survival, resource selection, and mortality risks associated with landscape features; 2) determine pheasant abundance as a function of remotely derived landscape composition and vegetative phenology; and 3) implement low-cost Arduino GPS trackers into our ring-necked pheasant study to improve fine-scale data collection. To accomplish these goals, we captured, collared, and tracked 100 female pheasants annually from December through March in each of three years (2016–2019). Overall, we captured 321 females and recorded 110 mortalities. We implemented low-cost GPS trackers on 35 individuals, resulting in 407 VHF locations and 1,574 GPS locations. This was a 287% increase in data density at only 23% increase in cost. We modeled weekly probability of survival and Cox proportional-hazard cause-specific mortality rates associated with landscape features. To understand pheasant distribution, we surveyed for and modeled pheasant abundance and distribution seasonally as a function of landscape composition and intraannual differences in vegetation phenology. Overwinter survival of pheasants (0.66) was highly influenced by snow depth. Pheasants using harvested fields experienced a 421% increase in risk of raptor predation. Additionally, pheasants using emergent wetlands experienced a 58% lower risk of weather mortality. Our distribution model demonstrated that proportion of Conservation Reserve Program grasslands, dormant wetlands, and 30- 40% row-crop agriculture within 1.6 km2 positively influenced pheasant abundance. Alternatively, pheasants were negatively associated with proportion of forests. Agricultural intensification is projected to continue reducing valuable concealment, grassland, and emergent wetland landscapes. As native perennial vegetation is critical to both pheasant abundance and winter survival, large-scale conservation efforts are critical to pheasant population viability. Innovative conservation solutions supplementing current farm bill policies may improve conservation adoption thereby improving pheasant abundance and overwinter survival

A study of turbulent flows and curved jets including application of the laser Doppler anemometry technique.

SIGLEAvailable from British Library Document Supply Centre- DSC:D87655 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Satellite tracking and earth dynamics research programs

The SAO laser site in Arequipa continued routine operations throughout the reporting period except for the months of March and April when upgrading was underway. The laser in Orroral Valley was operational through March. Together with the cooperating stations in Wettzell, Grasse, Kootwikj, San Fernando, Helwan, and Metsahove the laser stations obtained a total of 37,099 quick-look observations on 978 passes of BE-C, Starlette, and LAGEOS. The Network continued to track LAGEOS at highest priority for polar motion and Earth rotation studies, and for other geophysical investigations, including crustal dynamics, Earth and ocean tides, and the general development of precision orbit determination. The Network performed regular tracking of BE-C and Starlette for refined determinations of station coordinate and the Earth's gravity field and for studies of solid earth dynamics. Monthly statistics of the passes and points are given by station and by satellite

Muon (g-2) Technical Design Report

The Muon (g-2) Experiment, E989 at Fermilab, will measure the muon anomalous magnetic moment a factor-of-four more precisely than was done in E821 at the Brookhaven National Laboratory AGS. The E821 result appears to be greater than the Standard-Model prediction by more than three standard deviations. When combined with expected improvement in the Standard-Model hadronic contributions, E989 should be able to determine definitively whether or not the E821 result is evidence for physics beyond the Standard Model. After a review of the physics motivation and the basic technique, which will use the muon storage ring built at BNL and now relocated to Fermilab, the design of the new experiment is presented. This document was created in partial fulfillment of the requirements necessary to obtain DOE CD-2/3 approval

Halogen occultation experiment intergrated test plan

The test program plan is presented for the Halogen Occultation Experiment (HALOE) instrument, which is being developed in-house at the Langley Research Center for the Upper Atmosphere Research Satellite (UARS). This comprehensive test program was developed to demonstrate that the HALOE instrument meets its performance requirements and maintains integrity through UARS flight environments. Each component, subsystem, and system level test is described in sufficient detail to allow development of the necessary test setups and test procedures. Additionally, the management system for implementing this test program is given. The HALOE instrument is a gas correlation radiometer that measures vertical distribution of eight upper atmospheric constituents: O3, HC1, HF, NO, CH4, H2O, NO2, and CO2

PATTERN EVALUATION FOR IN-PLANE DISPLACEMENT MEASUREMENT OF THIN FILMS

The term Gossamer is used to describe ultra-lightweight spacecraft structures that solve the aerospace challenge of obtaining maximum performance while reducing the launch costs of the spacecraft. Gossamer structures are extremely compliant, which complicates control design and ground testing in full scale. One approach is to design and construct smaller test articles and verify their computational models experimentally, so that similar computational models can be used to predict the dynamic performance of full-scale structures. Though measurement of both in-plane and out-of-plane displacements is required to characterize the dynamic response of the surface of these structures, this thesis lays the groundwork for dynamic measurement of the in-plane component. The measurement of thin films must be performed using non-contacting sensors because any contacting sensor would change the dynamics of the structure. Moreover, the thin films dealt with in this work are coated with either gold or aluminum for special applications making the film optically smooth and therefore requiring a surface pattern. A Krypton Fluoride excimer laser system was selected to fabricate patterns on thin-film mirror test articles. Parameters required for pattern fabrication were investigated. Effects of the pattern on the thin-film dynamics were studied using finite element analysis. Photogrammetry was used to study the static in-plane displacement of the thin-film mirror. This was performed to determine the feasibility of the photogrammetric approach for future dynamic tests. It was concluded that photogrammetry could be used efficiently to quantify dynamic in-plane displacement with high-resolution cameras and sub-pixel target marking