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..

A Tomada de Decisão (Bio)ética: Estudo Preliminar Utilizando o Mobile Eye Tracking

RESUMO A tomada de decisão é uma das dimensões essenciais da formação do profissional da saúde, como mencionado nas atuais Diretrizes Curriculares Nacionais do Curso de Graduação em Medicina. O processo decisório, no âmbito da saúde, envolve diferentes aspectos, incluindo os elementos (bio)éticos. Nesse sentido, pesquisas que investiguem a tomada de decisão em (bio)ética poderão elucidar passos ainda não completamente esclarecidos, permitindo uma construção mais efetiva das competências em (bio)ética, na graduação e na pós-graduação. Diante desta perspectiva, o objetivo deste estudo é explorar possibilidades de uso do Mobile Eye Tracking para o estudo do papel da atenção visual – durante a exibição de filmes de cinema – no processo decisório em (bio)ética.

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.

Design and development of the architecture of an agricultural mobile robot

Parameters such as tolerance, scale and agility utilized in data sampling for using in Precision Agriculture required an expressive number of researches and development of techniques and instruments for automation. It is highlighted the employment of methodologies in remote sensing used in coupled to a Geographic Information System (GIS), adapted or developed for agricultural use. Aiming this, the application of Agricultural Mobile Robots is a strong tendency, mainly in the European Union, the USA and Japan. In Brazil, researches are necessary for the development of robotics platforms, serving as a basis for semi-autonomous and autonomous navigation systems. The aim of this work is to describe the project of an experimental platform for data acquisition in field for the study of the spatial variability and development of agricultural robotics technologies to operate in agricultural environments. The proposal is based on a systematization of scientific work to choose the design parameters utilized for the construction of the model. The kinematic study of the mechanical structure was made by the virtual prototyping process, based on modeling and simulating of the tension applied in frame, using the.

IDENTIFICATION OF SUITABLE AREAS FOR IRRIGATED RICE CROPPING USING MODIS IMAGES AND HAND MODEL

ABSTRACT One of the most relevant activities of Brazilian economy is agriculture. Among the main crops in Brazil, rice is one of high relevance. The state of Rio Grande do Sul, in Southern Brazil, is responsible for 68.7% of domestic production (IBGE, 2013). The goal of this study was to develop a low-cost methodology with a regional scope to identify suitable areas for irrigated rice cropping in this state, using spectro-temporal behavior of vegetation index by means of MODIS images and HAND model. The rice-cropped area of this study was the southern half of the State. Using the HAND model, flood areas were mapped to identify irrigated rice cultivation. We used multi-temporal images of vegetation index from MODIS sensor, covering the period from August 2001 to May 2012. To assess the results, we used data collected in the fields and cropped area information from IBGE. The results showed that the proposed methodology was satisfactory, with Kappa 0.92 and global accuracy of 98.18%. As result, MODIS sensor data and flood areas delineation by means of HAND model generated the estimate irrigated rice area for the area of study.

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.

Design and implementation of robot gripper interface

This thesis presents a design for an asynchronous interface to Robotiq adaptive gripper s-model. Designed interface is a communication layer that works on top of modbus layer. The design contains function definitions, finite state machine and exceptions. The design was not fully implemented but enough was so that it can be used. The implementation was done with c++ in linux environment. Additionally to the implementation a simple demo program was made to show the interface is used. Also grippers closing speed and force were measured. There is also a brief introduction into robotics and robot grasping.

Four-arm single docking full robotic surgery for low rectal cancer: technique standardization

The authors present the four-arm single docking full robotic surgery to treat low rectal cancer. The eight main operative steps are: 1- patient positioning; 2- trocars set-up and robot docking; 3- sigmoid colon, left colon and splenic flexure mobilization (lateral-to-medial approach); 4-Inferior mesenteric artery and vein ligation (medial-to-lateral approach); 5- total mesorectum excision and preservation of hypogastric and pelvic autonomic nerves (sacral dissection, lateral dissection, pelvic dissection); 6- division of the rectum using an endo roticulator stapler for the laparoscopic performance of a double-stapled coloanal anastomosis (type I tumor); 7- intersphincteric resection, extraction of the specimen through the anus and lateral-to-end hand sewn coloanal anastomosis (type II tumor); 8- cylindric abdominoperineal resection, with transabdominal section of the levator muscles (type IV tumor). The techniques employed were safe and have presented low rates of complication and no mortality.

Novel Methods for Error Modeling and Parameter Identification of a Redundant Serial-Parallel Hybrid Robot

To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements， but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.

Alitajunta ei ole kaikille sama : neosurrealismi, anarkia ja uusi taide - John Richardsonin kirja An Eye for Music avaa näkökulmia digitaalisen ajan surrealismille

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