Mobile robot localization using sonar ranging and wlan intensity maps

 Main goal of this thesis was to implement a localization system which uses sonars and WLAN intensity maps to localize an indoor mobile robot. A probabilistic localization method, Monte Carlo Localization is used in localization. Also the theory behind probabilistic localization is explained. Two main problems in mobile robotics, path tracking and global localization, are solved in this thesis. Implemented system can achieve acceptable performance in path tracking. Global localization using WLAN received signal strength information is shown to provide good results, which can be used to localize the robot accurately, but also some bad results, which are no use when trying to localize the robot to the correct place. Main goal of solving ambiguity in office like environment is achieved in many test cases.

Simulation Supported Robot Programming using XML

The main objective of this master's thesis is to study robot programming using simulation software, and also how to embed the simulation software into company's own robot controlling software. The further goal is to study a new communication interface to the assembly line's components -more precisely how to connect the robot cell into this new communication system. Conveyor lines are already available where the conveyors use the new communication standard. The robot cell is not yet capable of communicating with to other devices using the new communication protocols. The main problem among robot manufacturers is that they all have their own communication systems and programming languages. There has not been any common programming language to program all the different robot manufacturers robots, until the RRS (Realistic Robot Simulation) standards were developed. The RRS - II makes it possible to create the robot programs in the simulation software and it gives a common user interface for different robot manufacturers robots. This thesis will present the RRS - II standard and the robot manufacturers situation for the RRS - II support. Thesis presents how the simulation software can be embedded into company's own robot controlling software and also how the robot cell can be connected to the CAMX (Computer Aided Manufacturing using XML) communication system.

Error Modeling and Accuracy Analysis of a Novel Mobile Hybrid Parallel Robot

Over the last decades, calibration techniques have been widely used to improve the accuracy of robots and machine tools since they only involve software modification instead of changing the design and manufacture of the hardware. Traditionally, there are four steps are required for a calibration, i.e. error modeling, measurement, parameter identification and compensation. The objective of this thesis is to propose a method for the kinematics analysis and error modeling of a newly developed hybrid redundant robot IWR (Intersector Welding Robot), which possesses ten degrees of freedom (DOF) where 6-DOF in parallel and additional 4-DOF in serial. In this article, the problem of kinematics modeling and error modeling of the proposed IWR robot are discussed. Based on the vector arithmetic method, the kinematics model and the sensitivity model of the end-effector subject to the structure parameters is derived and analyzed. The relations between the pose (position and orientation) accuracy and manufacturing tolerances, actuation errors, and connection errors are formulated. Computer simulation is performed to examine the validity and effectiveness of the proposed method.

OLED-teknologia silmänäytössä ja linssiokulaarin korvaaminen muoviprismalla

Tämä diplomityö esittelee monikäyttöisen kamerajärjestelmän, mikä on pääsääntöisesti tarkoitettu valovahvistimen perään integroitavaksi. Tarkoituksena on parantaa sotilaan pimeätoimintakykyä ja urbaanissa ympäristössä operointia. Järjestelmän yhtenä moduulina on silmänäyttö, joka perustuu itse-emittoivaan orgaaniseen LED-näyttöelementtiin ja perinteiseen okulaarioptiikkaan. Työssä tutustutaan näyttöelementin teknologiaan, sen mahdollisiin rajoituksiin sekä selvitetään optisilla mittauksilla, voitaisiinko konventionaalinen linssiokulaari korvata muovisella prismaokulaarilla. Tämä mahdollistaisi pienemmän ja kevyemmän silmänäytön kehittämisen, mikä parantaisi kamerajärjestelmän käytettävyyttä ja kilpailukykyä.

Performance Evaluation and Calibration of Machine Vision Measurement

This thesis presents the calibration and comparison of two systems, a machine vision system that uses 3 channel RGB images and a line scanning spectral system. Calibration. is the process of checking and adjusting the accuracy of a measuring instrument by comparing it with standards. For the RGB system self-calibrating methods for finding various parameters of the imaging device were developed. Color calibration was done and the colors produced by the system were compared to the known colors values of the target. Software drivers for the Sony Robot were also developed and a mechanical part to connect a camera to the robot was also designed. For the line scanning spectral system, methods for the calibrating the alignment of the system and the measurement of the dimensions of the line scanned by the system were developed. Color calibration of the spectral system is also presented.

Sinfonia da camera

Digitoitu 9. 9. 2008.

Use of neural networks in robot positioning of large flexible redundant manipulators

Deflection compensation of flexible boom structures in robot positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid structure. The number of table values increases greatly if the working area of the boom is large and the required positioning accuracy is high. The inverse kinematics problems are very nonlinear, and if the structure is redundant, in some cases it cannot be solved in a closed form. If the structural flexibility of the manipulator arms is taken into account, the problem is almost impossible to solve using analytical methods. Neural networks offer a possibility to approximate any linear or nonlinear function. This study presents four different methods of using neural networks in the static deflection compensation and inverse kinematics solution of a flexible hydraulically driven manipulator. The training information required for training neural networks is obtained by employing a simulation model that includes elasticity characteristics. The functionality of the presented methods is tested based on the simulated and measured results of positioning accuracy. The simulated positioning accuracy is tested in 25 separate coordinate points. For each point, the positioning is tested with five different mass loads. The mean positioning error of a manipulator decreased from 31.9 mm to 4.1 mm in the test points. This accuracy enables the use of flexible manipulators in the positioning of larger objects. The measured positioning accuracy is tested in 9 separate points using three different mass loads. The mean positioning error decreased from 10.6 mm to 4.7 mm and the maximum error from 27.5 mm to 11.0 mm.

Novel Robot Solutions for Carrying out Field Joint Welding and Machining in the Assembly of the Vacuum Vessel of ITER

It is necessary to use highly specialized robots in ITER (International Thermonuclear Experimental Reactor) both in the manufacturing and maintenance of the reactor due to a demanding environment. The sectors of the ITER vacuum vessel (VV) require more stringent tolerances than normally expected for the size of the structure involved. VV consists of nine sectors that are to be welded together. The vacuum vessel has a toroidal chamber structure. The task of the designed robot is to carry the welding apparatus along a path with a stringent tolerance during the assembly operation. In addition to the initial vacuum vessel assembly, after a limited running period, sectors need to be replaced for repair. Mechanisms with closed-loop kinematic chains are used in the design of robots in this work. One version is a purely parallel manipulator and another is a hybrid manipulator where the parallel and serial structures are combined. Traditional industrial robots that generally have the links actuated in series are inherently not very rigid and have poor dynamic performance in high speed and high dynamic loading conditions. Compared with open chain manipulators, parallel manipulators have high stiffness, high accuracy and a high force/torque capacity in a reduced workspace. Parallel manipulators have a mechanical architecture where all of the links are connected to the base and to the end-effector of the robot. The purpose of this thesis is to develop special parallel robots for the assembly, machining and repairing of the VV of the ITER. The process of the assembly and machining of the vacuum vessel needs a special robot. By studying the structure of the vacuum vessel, two novel parallel robots were designed and built; they have six and ten degrees of freedom driven by hydraulic cylinders and electrical servo motors. Kinematic models for the proposed robots were defined and two prototypes built. Experiments for machine cutting and laser welding with the 6-DOF robot were carried out. It was demonstrated that the parallel robots are capable of holding all necessary machining tools and welding end-effectors in all positions accurately and stably inside the vacuum vessel sector. The kinematic models appeared to be complex especially in the case of the 10-DOF robot because of its redundant structure. Multibody dynamics simulations were carried out, ensuring sufficient stiffness during the robot motion. The entire design and testing processes of the robots appeared to be complex tasks due to the high specialization of the manufacturing technology needed in the ITER reactor, while the results demonstrate the applicability of the proposed solutions quite well. The results offer not only devices but also a methodology for the assembly and repair of ITER by means of parallel robots.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Mobile Teleoperation of a Mobile Robot

This thesis describes the design and implementation of a graphical application on a mobile device to teleoperate a mobile robot. The department of information technology in Lappeenranta University conducts research in robotics, and the main motivation was to extend the available teleoperation applications for mobile devices. The challenge was to port existing robot software library onto an embedded device platform, then develop a suitable user interface application that provides sufficient functionality to perform teleoperation tasks over a wireless communication network. This thesis involved investigating previous teleoperation applications and conducted similar experiments to test and evaluate the designed application for functional activity and measure performance on a mobile device which have been identified and achieved. The implemented solution offered good results for navigation purposes particularly for teleoperating a visible robot and suggests solutions for exploration when no environment map for the operator is present.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

Effect of pulps fractionation on formation and strength properties of laboratory hand sheets

The objectives of the work were to study the effect of dewatering time varying on formation properties of papersheets, to determine the role of fines fraction in creation of paper with good formation and strength properties of papersheets, and also to study the effect of charge modification of fibers fractionations on formation properties of handsheets. The paper formation is one of the most important structural properties of paper. This property has effect on physical and optical characteristics of paper. In thi work the effect of formation on tensile strength was determined. The formation properties were analyzed by using the AMBERTEC Beta Formation Tester. The PAM addition as a f;locculant agent did some changes in the formation of paper. Paper sheets were also made from different furnishes of both birch and pine pulps. The fibers particles as a fines have great effect on drainability changes. Fines fraction played important role in papermaking. The two kinds of pulps (pine and birch pulps) were also used in this work for investigation of fines role. As it was expected the fines fraction gave positive effect on paper formation, but when fines fraction was added above initial fines content the formation of paper was deteriorated. The effect of paper formation on tensile strength was also determined. In many cases the poor formation of paper had negative effect on strength properties of paper..

Reading Development During Elementary School Years. Evidence from Eye Movements

The present dissertation examined reading development during elementary school years by means of eye movement tracking. Three different but related issues in this field were assessed. First of all, the development of parafoveal processing skills in reading was investigated. Second, it was assessed whether and to what extent sublexical units such as syllables and morphemes are used in processing Finnish words and whether the use of these sublexical units changes as a function of reading proficiency. Finally, the developmental trend in the speed of visual information extraction during reading was examined. With regard to parafoveal processing skills, it was shown that 2nd graders extract letter identity information approx. 5 characters to the right of fixation, 4th graders approx. 7 characters to the right of fixation, and 6th graders and adults approx. 9 characters to the right of fixation. Furthermore, it was shown that all age groups extract more parafoveal information within compound words than across adjectivenoun pairs of similar length. In compounds, parafoveal word information can be extracted in parallel with foveal word information, if the compound in question is of high frequency. With regard to the use of sublexical units in Finnish word processing, it was shown that less proficient 2nd graders use both syllables and morphemes in the course of lexical access. More proficient 2nd graders as well as older readers seem to process words more holistically. Finally, it was shown that 60 ms is enough for 4th graders and adults to extract visual information from both 4-letter and 8-letter words, whereas 2nd graders clearly needed more than 60 ms to extract all information from 8- letter words for processing to proceed smoothly. The present dissertation demonstrates that Finnish 2nd graders develop their reading skills rapidly and are already at an adult level in some aspects of reading. This is not to say that there are no differences between less proficient (e.g., 2nd graders) and more proficient readers (e.g., adults) but in some respects it seems that the visual system used in extracting information from the text is matured by the 2nd grade. Furthermore, the present dissertation demonstrates that the allocation of attention in reading depends much on textual properties such as word frequency and whether words are spatially unified (as in compounds) or not. This flexibility of the attentional system naturally needs to be captured in word processing models. Finally, individual differences within age groups are quite substantial but it seems that by the end of the 2nd grade practically all Finnish children have reached a reasonable level of reading proficiency.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Tactile-Proprioceptive Robotic Grasping

Robotic grasping has been studied increasingly for a few decades. While progress has been made in this field, robotic hands are still nowhere near the capability of human hands. However, in the past few years, the increase in computational power and the availability of commercial tactile sensors have made it easier to develop techniques that exploit the feedback from the hand itself, the sense of touch. The focus of this thesis lies in the use of this sense. The work described in this thesis focuses on robotic grasping from two different viewpoints: robotic systems and data-driven grasping. The robotic systems viewpoint describes a complete architecture for the act of grasping and, to a lesser extent, more general manipulation. Two central claims that the architecture was designed for are hardware independence and the use of sensors during grasping. These properties enables the use of multiple different robotic platforms within the architecture. Secondly, new data-driven methods are proposed that can be incorporated into the grasping process. The first of these methods is a novel way of learning grasp stability from the tactile and haptic feedback of the hand instead of analytically solving the stability from a set of known contacts between the hand and the object. By learning from the data directly, there is no need to know the properties of the hand, such as kinematics, enabling the method to be utilized with complex hands. The second novel method, probabilistic grasping, combines the fields of tactile exploration and grasp planning. By employing well-known statistical methods and pre-existing knowledge of an object, object properties, such as pose, can be inferred with related uncertainty. This uncertainty is utilized by a grasp planning process which plans for stable grasps under the inferred uncertainty.