A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots

Localization and Mapping are two of the most important capabilities for autonomous mobile robots and have been receiving considerable attention from the scientific computing community over the last 10 years. One of the most efficient methods to address these problems is based on the use of the Extended Kalman Filter (EKF). The EKF simultaneously estimates a model of the environment (map) and the position of the robot based on odometric and exteroceptive sensor information. As this algorithm demands a considerable amount of computation, it is usually executed on high end PCs coupled to the robot. In this work we present an FPGA-based architecture for the EKF algorithm that is capable of processing two-dimensional maps containing up to 1.8 k features at real time (14 Hz), a three-fold improvement over a Pentium M 1.6 GHz, and a 13-fold improvement over an ARM920T 200 MHz. The proposed architecture also consumes only 1.3% of the Pentium and 12.3% of the ARM energy per feature.

A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection

This paper proposes a parallel hardware architecture for image feature detection based on the Scale Invariant Feature Transform algorithm and applied to the Simultaneous Localization And Mapping problem. The work also proposes specific hardware optimizations considered fundamental to embed such a robotic control system on-a-chip. The proposed architecture is completely stand-alone; it reads the input data directly from a CMOS image sensor and provides the results via a field-programmable gate array coupled to an embedded processor. The results may either be used directly in an on-chip application or accessed through an Ethernet connection. The system is able to detect features up to 30 frames per second (320 x 240 pixels) and has accuracy similar to a PC-based implementation. The achieved system performance is at least one order of magnitude better than a PC-based solution, a result achieved by investigating the impact of several hardware-orientated optimizations oil performance, area and accuracy.

Characterization of a beta-1,3-glucanase active in the alkaline midgut of Spodoptera frugiperda larvae and its relation to beta-glucan-binding proteins

Spodoptera frugiperda beta-1,3-glucanase (SLam) was purified from larval midgut. It has a molecular mass of 37.5 kDa, an alkaline optimum pH of 9.0, is active against beta-1,3-glucan (laminarin), but cannot hydrolyze yeast beta-1,3-1,6-glucan or other polysaccharides. The enzyme is an endoglucanase with low processivity (0.4), and is not inhibited by high concentrations of substrate. In contrast to other digestive beta-1,3-glucanases from insects, SLam is unable to lyse Saccharomyces cerevisae cells. The cDNA encoding SLam was cloned and sequenced, showing that the protein belongs to glycosyl hydrolase family 16 as other insect glucanases and glucan-binding proteins. Multiple sequence alignment of beta-1,3-glucanases and beta-glucan-binding protein supports the assumption that the beta-1,3-glucanase gene duplicated in the ancestor of mollusks and arthropods. One copy originated the derived beta-1,3-glucanases by the loss of an extended N-terminal region and the beta-glucan-binding proteins by the loss of the catalytic residues. SLam homology modeling suggests that E228 may affect the ionization of the catalytic residues, thus displacing the enzyme pH optimum. SLam antiserum reacts with a single protein in the insect midgut. Immunocytolocalization shows that the enzyme is present in secretory vesicles and glycocalyx from columnar cells. (C) 2010 Elsevier Ltd. All rights reserved.

Mapeamento de ambientes estruturados com extração de informações geométricas através de dados sensoriais

The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose

Localização e mapeamento simultâneos de ambientes planos usando visão monocular e representação híbrida do ambiente

The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping) solution based on Extended Kalman Filter (EKF) in order to make possible a robot navigates along the environment using information from odometry and pre-existing lines on the floor. Initially, a segmentation step is necessary to classify parts of the image in floor or non floor . Then the image processing identifies floor lines and the parameters of these lines are mapped to world using a homography matrix. Finally, the identified lines are used in SLAM as landmarks in order to build a feature map. In parallel, using the corrected robot pose, the uncertainty about the pose and also the part non floor of the image, it is possible to build an occupancy grid map and generate a metric map with the obstacle s description. A greater autonomy for the robot is attained by using the two types of obtained map (the metric map and the features map). Thus, it is possible to run path planning tasks in parallel with localization and mapping. Practical results are presented to validate the proposal

Navegação cooperativa de um robô humanóide e um robô com rodas usando informação visual

This work presents a cooperative navigation systemof a humanoid robot and a wheeled robot using visual information, aiming to navigate the non-instrumented humanoid robot using information obtained from the instrumented wheeled robot. Despite the humanoid not having sensors to its navigation, it can be remotely controlled by infra-red signals. Thus, the wheeled robot can control the humanoid positioning itself behind him and, through visual information, find it and navigate it. The location of the wheeled robot is obtained merging information from odometers and from landmarks detection, using the Extended Kalman Filter. The marks are visually detected, and their features are extracted by image processing. Parameters obtained by image processing are directly used in the Extended Kalman Filter. Thus, while the wheeled robot locates and navigates the humanoid, it also simultaneously calculates its own location and maps the environment (SLAM). The navigation is done through heuristic algorithms based on errors between the actual and desired pose for each robot. The main contribution of this work was the implementation of a cooperative navigation system for two robots based on visual information, which can be extended to other robotic applications, as the ability to control robots without interfering on its hardware, or attaching communication devices

Localização de robôs móveis autônomos utilizando fusão sensorial de odometria e visão monocular

The development and refinement of techniques that make simultaneous localization and mapping (SLAM) for an autonomous mobile robot and the building of local 3-D maps from a sequence of images, is widely studied in scientific circles. This work presents a monocular visual SLAM technique based on extended Kalman filter, which uses features found in a sequence of images using the SURF descriptor (Speeded Up Robust Features) and determines which features can be used as marks by a technique based on delayed initialization from 3-D straight lines. For this, only the coordinates of the features found in the image and the intrinsic and extrinsic camera parameters are avaliable. Its possible to determine the position of the marks only on the availability of information of depth. Tests have shown that during the route, the mobile robot detects the presence of characteristics in the images and through a proposed technique for delayed initialization of marks, adds new marks to the state vector of the extended Kalman filter (EKF), after estimating the depth of features. With the estimated position of the marks, it was possible to estimate the updated position of the robot at each step, obtaining good results that demonstrate the effectiveness of monocular visual SLAM system proposed in this paper

Técnicas visuais de localização e mapeamento simultâneos sem extração de primitivas geométricas da imagem

In Simultaneous Localization and Mapping (SLAM - Simultaneous Localization and Mapping), a robot placed in an unknown location in any environment must be able to create a perspective of this environment (a map) and is situated in the same simultaneously, using only information captured by the robot s sensors and control signals known. Recently, driven by the advance of computing power, work in this area have proposed to use video camera as a sensor and it came so Visual SLAM. This has several approaches and the vast majority of them work basically extracting features of the environment, calculating the necessary correspondence and through these estimate the required parameters. This work presented a monocular visual SLAM system that uses direct image registration to calculate the image reprojection error and optimization methods that minimize this error and thus obtain the parameters for the robot pose and map of the environment directly from the pixels of the images. Thus the steps of extracting and matching features are not needed, enabling our system works well in environments where traditional approaches have difficulty. Moreover, when addressing the problem of SLAM as proposed in this work we avoid a very common problem in traditional approaches, known as error propagation. Worrying about the high computational cost of this approach have been tested several types of optimization methods in order to find a good balance between good estimates and processing time. The results presented in this work show the success of this system in different environments

World of Unknown Creatures and Their Hidden Works

What is the most mysterious feelings in mankind? What is the most general way by which every mankind is subject to change. Well monotonous, and steady life where someone does the same kind of work at same pace in same time, without any change of events, creates the burdensome feeling in a person. Yet people are unaware of it. We don't know where are we going, yet we go at the same pace, since in practical sense we are getting some credit for something. But the thing how much do we keep up, and maintain the balance in nature, so that we can really feel the value and the quality of life, and know the exact happiness of fulfilling the work. But if its totally becomes materialistic, and emotional aspect goes away from human beings, where social talking never goes away from your duties. Then!!!! ... I mean there is no need of human beings. If we are so developed, right from past few centuries and our domination, had created a modern social world, then we can create all kinds of devices and software which can handle all the works for which the people don't have to stay overtime just to finish that. I mean in that way human life will move through some progress, and will have some development. But the environment where we are living nothing new or development is taking place as the work becomes a duty for human being but not to machine which should be given some task to be completed.So all those devices are not in the society, since human being is already taking charge if it.

My life as a clone

Zehar, an extremely popular and dignified man, is a renowned scientist. He has worked extremely hard, and spend two years, on a research to make human cloning.His idea was to produce the creature, simply of its own looking and exactly identical as him. To his satisfaction he had accomplished to make the physical characteristic, simply like his own. Even his experiment on a mentality and emotional aspect of a clone was also a success. But his last and the most vital wish, remained a complete failure. He wanted that the soul of the cloning should also be identical like his own soul, as the physical characteristics. But it was a complete different. The character of the cloning was getting too dangerous and later part he found he has to lose all his sympathy of his own clone, as his clone had became the most dangerous enemy in his life. All his fame and his moral character is being uprooted to the public by his clone. Ultimately he decides to kill it, and clone even takes a motto to kill Zehar, if Zehar decides to kill it, simply because, the clone wants to create his own fame to rule the world. Thus the story, gives an advice, to the world of science, that not to try human clones, in particular.

Semantic Enrichment of Scientific Documents with Semantic Lenses – Developing methodologies, tools and prototypes for their concrete use

Con questa dissertazione di tesi miro ad illustrare i risultati della mia ricerca nel campo del Semantic Publishing, consistenti nello sviluppo di un insieme di metodologie, strumenti e prototipi, uniti allo studio di un caso d‟uso concreto, finalizzati all‟applicazione ed alla focalizzazione di Lenti Semantiche (Semantic Lenses).

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Ricostruzione 3d da immagini rgb-d su piattaforma mobile

Viene proposto un porting su piattaforma mobile Android di un sistema SLAM (Simultaneous Localization And Mapping) chiamato SlamDunk. Il porting affronta problematiche di prestazioni e qualità delle ricostruzioni 3D ottenute, proponendo poi la soluzione ritenuta ottimale.

Sviluppo di algoritmi di autolocalizzazione su dispositivi mobili

Negli ultimi anni, complice la rapida evoluzione degli elaboratori e dei sensori, spinta dal mercato smartphone, una tecnologia si sta sviluppando e si sta diffondendo rapidamente. Si tratta di quella relativa agli unmanned vehicles (UV), i veicoli senza pilota, spesso nel linguaggio comune chiamati “droni”. Questi particolari veicoli sono dotati della tecnologia adatta per svolgere in relativa autonomia particolari mansioni, senza la necessità della presenza di un pilota a bordo. In questa Tesi magistrale si descrivono brevemente le diverse categorie di UV e l’attuale livello di autonomia raggiunta nello svolgimento di alcune funzioni, grazie a tecnologie quali i linguaggi ad agenti, di cui si presentano anche alcune significative applicazioni allo stato dell’arte. Per rendere più efficaci eventuali nuove funzionalità, fornendo una metodologia di sviluppo, atta ad aumentare il grado di astrazione, viene proposto un approccio architetturale a tre livelli. In particolare, viene approfondito il secondo livello, presentando l’implementazione di una funzionalità, l’autolocalizzazione spaziale, utile ad un sistema di terzo livello per arricchire la propria conoscenza dell’ambiente, al fine di raggiungere la massima autonomia nel controllo del mezzo. Questa prima esperienza ha consentito di approfondire le necessità in termini di hardware e software, al fine di poter effettuare una scelta mirata per l’ottimizzazione dei risultati ed un eventuale porting on-board, nella prospettiva di svincolare il mezzo da eventuali collegamenti con una stazione di terra, fino ad ora necessaria per eseguire le attività più complesse. Un interessante caso di studio consente di verificare la bontà del modello proposto e i risultati raggiunti nell’autolocalizzazione. In conclusione, si propongono ulteriori sviluppi che potranno fornire gli strumenti necessari alla massima espressione del potenziale che gli UV possiedono.

Louder than a bomb: quando le parole sono più forti di una bomba. Proposta di traduzione di testi scelti.

Questo elaborato ha lo scopo di presentare la “slam poetry”, una disciplina con la quale solo recentemente il pubblico italiano si è confrontato. Spiegherò di cosa si tratta, quando e perché si è originata, come si è evoluta e perché ha avuto così tanto successo con alcune categorie di persone. Non mancherà anche una riflessione generale sulla traduzione della poesia e verrà dato abbondante spazio alle propostedi traduzione di alcuni brani di slam poetry, scelti tra quelli partecipanti al concorso di Chicago del 2008, con relativo commento alla traduzione.