Detta projekt har utförts på monteringslinan i Volvo Construction Equipment (VCE), Hallsberg. Där har man en robotcell som arbetar i samspel med limstationerna 17&18. Utav 4 hyttfamiljer limmas och monteras glasrutor till 3 av hyttfamiljerna manuellt. Robotcellen limmar glasrutorna för 1 hyttfamilj som har 2 typer av hytter, med en cykeltid på 8,4–9,5 min. Då takttiden ligger på 7,5 min/hytt för resten av linan anses limstationerna vara en trång sektor enligt VCE. Med en ökad framtida produktvariation och ett ökat kundbehov anser VCE att den trånga sektorn har förutsättningarna för att bli en framtida flaskhals då takttiden ska ner till 7,2 min/hytt till år 2020. Med hjälp av Leanprinciper och Sex Sigma verktyg har projektutförarna avhandlat frågeställningen "Hur kan robotcellen effektiviseras med avseende på cykeltid och framtida produktvariation?". Genom en framtagning av en nulägesanalys med hjälp av tidmätningar, intervjuer och teoriinsamling kunde sedan en värdeflödeskarta skapas. Genom rotorsaksanalyser på icke-värdeskapande men nödvändiga aktiviteter kunde ett förbättringsförslag presenteras med en uppskattad cykeltid på mindre än 7–7,6 min. Detta med hjälp av en hanteringsrobot och en limrobot som har separata aktiviteter som är parallella, istället för att ha en robot som har samtliga aktiviteter som i nuläget. Projektutförarna rekommenderar att VCE för arbetet vidare genom att- ta reda på hur lång tid det tar för en automatiserad limning av glasrutor till samtliga hyttyper, - undersöka hur snabbt hanteringsroboten behöver arbeta i förhållande till limroboten för att tillfredsställa behovet av glasrutor för limroboten, - undersöka hur kasserade glasrutor från robotcellerna påverkar monteringsflödet samt - undersöka utvecklingsmöjligheter för att effektivisera den enda värdeskapande aktiviteten för limroboten med avseende på cykeltid. / This project has been carried out on the assembly line in Volvo Construction Equipment (VCE), Hallsberg. A robotic cell is located in the assembly line and works in conjunction with the glue stations 17 & 18. Out of 4 cab families, windows are glued and mounted to 3 of the cab families manually. The robotic cell glues the windows for 1 cab family that has 2 types of cabs, with a cycle time of 8.4-9.5 min. Since the takt time is 7.5 min/cab in the other sections of the assembly line, the glue stations are considered a narrow sector according to VCE. With increased future product variability and increased customer demand, VCE considers that the narrow sector has the prerequisites for becoming a future bottleneck, as the takt time will drop to 7.2 min/cab to 2020. With the help of Lean principles and Six Sigma tools, project executives have dealt with the question "How can the robotic cell be made more efficient with respect to cycle time and future product variability?”. Through a current state analysis by means of time measurements, interviews and theory collection, a value-flow chart could then be created. By root cause analysis on non-value-adding but necessary activities an improvement proposal could be presented with an estimated cycle time of less than 7-7.6 min. The thesis workers propose that VCE goes ahead by- finding out how long an automated gluing of windows take (for all cabs),- examining how fast the handling robot needs to work in relation to the glue robot (to satisfy the need for windows for the glue robot),- examining how discarded windows from the robotic cells affect the assembly flow, and- investigating the opportunities to streamline the only value-creating activity for the glue robot with regards to cycle time.

Orientador: Suely Cunha Amaro Mantovani / Resumo: No estudo dos manipuladores são utilizados os conceitos da cinemática direta e a inversa. No cálculo da cinemática direta tem-se a facilidade da notação de Denavit-Hartenberg, mas o desafio maior é a resolução da cinemática inversa, que se torna mais complexa conforme aumentam os graus de liberdade do manipulador, além de apresentar múltiplas soluções. As variáveis angulares obtidas pelas equações da cinemática inversa são utilizadas pelo controlador, para posicionar o órgão terminal do manipulador em um ponto específico de seu volume de trabalho. Na busca de alternativas para contornar estes problemas, neste trabalho utilizam-se os Modelos Adaptativos de Inferência Neuro-Fuzzy - ANFIS para a resolução da cinemática inversa, por meio de simulações, para obter o posicionamento de um manipulador robótico de 5 graus de liberdade, composto por sete servomotores controlados pela plataforma de desenvolvimento Intel® Galileo Gen 2, usado como caso de estudo. Nas simulações usamse ANFIS com uma arquitetura com três e quatro funções de pertinência de entrada, do tipo gaussiana. O desempenho da arquitetura da ANFIS implementada foi comparado com uma Rede Perceptron Multicamadas, demonstrando com os resultados favoráveis a ANFIS, a sua capacidade de aprender e resolver com baixo erro quadrático médio e com precisão, a cinemática inversa para o manipulador em estudo. Verifica-se também, que a performance das ANFIS melhora, quanto à precisão dos resultados, demonstrado pelo desvio médio d... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In the study of manipulator’s, the concepts of direct and inverse kinematics are used. In the computation of forward kinematics, it has of the ease of Denavit-Hartenberg notation, but the biggest challenge is the resolution of the inverse kinematics, which becomes more complex as the manipulator's degrees of freedom increase, besides presenting multiple solutions. The angular variables obtained by the inverse kinematics equations are used by the controller to position the terminal organ of the manipulator at a specific point in its work volume. In the search for alternatives to overcome these problems, in this work, the Adaptive Neuro-Fuzzy Inference Models (ANFIS) are used to solve the inverse kinematics, by means of simulations, to obtain the positioning of a robot manipulator of 5 degrees of freedom, consisting of seven servomotors controlled by the Intel® Galileo Gen 2 development platform, used as a case's study . In the simulations ANFIS's architecture are used three and four Gaussian membership functions of input. The performance of the implemented ANFIS architecture was compared to a Multi-layered Perceptron Network, demonstrating with the favorable results the ANFIS, its ability to learn and solve with low mean square error and with precision, the inverse kinematics for the manipulator under study. It is also verified that the performance of the ANFIS improves, as regards the accuracy of the results in the training process, , demonstrated by the mean deviation of the... (Complete abstract click electronic access below) / Mestre

A mechatronic chewing robot of 6-DOF mechanism which consists mainly of the skull, six crank actuators, end effector and motion control system has been designed and is required to simulate human chewing behaviours while the chewed food properties are evaluated. The robotic mechanism is proposed and its kinematic parameters are defined according to the biomechanical findings and measurements of the human masticatory system. This thesis is concerned with the design and implementation of trajectory tracking control for robotic jaw actuators via Galil motion controller. The aim of this project is to simulate the dynamics behaviour and force-motion control of the robot, and to quantitatively assess food texture changes during chewing. A control system based Galil motion control card has been formed to achieve the motion of simulated human mastication. Some real human mastication motion have been tracked and used as targeted trajectories for the robot to reproduce. Several experiments have been executed to measure the jaw movements and chewing forces. To reduce the vibration of the actuators and protect sensitive linkage part of the robot, the traditional PID control and some advanced control theories were implemented to achieve most effective efforts. A mathematical model was also designed at the first stage when a test actuator powered by brushless motor was formed; however, it is finally proven not well controlled in either mechanical and control ways. Major features of the built robot including the motion control system are presented and tested. Experimental results including free chewing, soft-food and hard-food chewing are given where the foods are simulated by foam and hard objects. Also the joint actuations and driving torques required are compared for the chewing of different foods. In conclusion, tracking motion control has been attempted on the physical robot and a solution to the trajectory control has been developed.

Design, production and development of individual mini/micro robots and then formation of their cooperative colony are the main topics of this thesis. The produced mini/micro robots are as small and light as possible. In addition, they are multifunctional (programmable), flexible and intelligent while maintaining a very low production cost. Mini/micro robots, called MinT-DB series are able to communicate with each other to work cooperatively. Moreover, these robots can be the basis for the future studies considering the application of artificial intelligence and modeling of live colonies in the nature. Traditional design, production and assembly techniques have been used widely up to now. However, none of them were related with the mini/micro scale. Therefore, this thesis can help people in understanding the difficulties of the design, production, and assembly of the mini/micro systems under the light of the reported science. In this thesis, instead of examining a specific application field of mini/micro robotic systems, a technology demonstrative work is carried out. Therefore, this thesis contributes to the mini/micro robotic technology, which is also very new and popular in today&amp / #8217 / s world, with the robots having the dimensions of 7.5x6x6 cm.

Robotics is an interdisciplinary subject and combines mechanical, computer and electrical engineering components together to solve different kinds of problems. In order to build robotic systems, these disciplines should be integrated. Therefore, mobile robots can be used as a tool in education for teaching engineering concepts. They can be employed to be used in undergraduate, graduate and doctorate research. Hands on experience on a mobile robot increase motivation of the students on the topic and give them precious practical knowledge. It also delivers students new skills like teamwork, problem solving, creativity, by executing robotic exercises. To be able to fulfill these outcomes, universities and research centers need mobile robot platforms that are modular, easy to build, cheap and flexible. However it should be also powerful and capable of being used in different research studies and hence be customizable depending on the requirements of these topics. This thesis aims at building an indoor mobile robot that can be used as a platform for developing algorithms involving various sensors incorporated onto a mobile platform. More precisely, it can be used as a base for indoor navigation and localization algorithms, as well as it can be used as platform for developing algorithms for larger autonomous mobile robots. The thesis work involves the design and manufacturing of a mobile robot platform that can potentially facilitate mobile robotics research that involves use of various hardware to develop and test different perception and navigation algorithms.

This dissertation presents a basic information-driven sensor management problem, referred to as treasure hunt, that is relevant to mobile-sensor applications such as mine hunting, monitoring, and surveillance. The objective is to classify/infer one or multiple fixed targets or treasures located in an obstacle-populated workspace by planning the path and a sequence of measurements of a robotic sensor installed on a mobile platform associated with the treasures distributed in the sensor workspace. The workspace is represented by a connectivity graph, where each node represents a possible sensor deployment, and the arcs represent possible sensor movements. A methodology is developed for planning the sensing strategy of a robotic sensor deployed. The sensing strategy includes the robotic sensor's path, because it determines which targets are measurable given a bounded field of view. Existing path planning techniques are not directly applicable to robots whose primary objective is to gather sensor measurements. Thus, in this dissertation, a novel approximate cell-decomposition approach is developed in which obstacles, targets, the sensor's platform and field of view are represented as closed and bounded subsets of an Euclidean workspace. The approach constructs a connectivity graph with observation cells that is pruned and transformed into a decision tree, from which an optimal sensing strategy can be computed. It is shown that an additive incremental-entropy function can be used to efficiently compute the expected information value of the measurement sequence over time. The methodology is applied to a robotic landmine classification problem and the board game of CLUE$^{\circledR}$. In the landmine detection application, the optimal strategy of a robotic ground-penetrating radar is computed based on prior remote measurements and environmental information. Extensive numerical experiments show that this methodology outperforms shortest-path, complete-coverage, random, and grid search strategies, and is applicable to non-overpass capable platforms that must avoid targets as well as obstacles. The board game of CLUE$^{\circledR}$ is shown to be an excellent benchmark example of treasure hunt problem. The test results show that a player implementing the strategies developed in this dissertation outperforms players implementing Bayesian networks only, Q-learning, or constraint satisfaction, as well as human players. / Dissertation

The implant surgery replaces missing tooth to regain functionality and look of the normal tooth after dental operation. Improper placement of implant increases recuperation periods and reduces functionality. The aim of this thesis is to design a passive haptic robotic arm to guide dentist during the implant surgery. In this thesis, the optimum design of the 6R passive haptic robotic arm is achieved. The methodology used in optimization problem involves minimization of end-effector side parasitic forces/torques while maximizing transparency of the haptic device. The transparency of haptic device is defined as realism of forces generated by device in real world compared to forces in virtual world. The multivariable objective function including dynamic equations of 6R robotic arm is derived and the constraints are determined using kinematic equations. The optimization problem is solved using SQP and GA. The link lengths and other relevant parameters along with the location of tool path are optimized. The end-effector parasitic torques/forces are significantly minimized. The results of two optimization techniques have proven to be nearly the same, thus a global optimum solution has been found in the search space. Main contribution of this study is to take spatial nonlinear dynamics into consideration to reduce parasitic torques. Also, a mechanical brake is designed as a passive actuator. The mechanical brake includes a cone based braking system actuated by DC motor. Three different prototypes are manufactured to test performance of the mechanical brake. The final design indicates that the mechanical brake can be used as passive actuators.

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The thesis deals with the optimal pose selection for geometric and elastostatic calibration for industrial robots employed in machining of large parts. Particular attention is paid to the improvement of robot positioning accuracy after compensation of the geometric and elastostatic errors. To meet the industrial requirements of machining operations, a new approach for calibration experiments design for serial and quasi-serial industrial robots is proposed. This approach is based on a new industry-oriented performance measure that evaluates the quality of calibration experiment plan via the manipulator positioning accuracy after error compensation, and takes into account the particularities of prescribed manufacturing task by introducing manipulator test-poses. Contrary to previous works, the developed approach employs an enhanced partial pose measurement method, which uses only direct position measurements from an external device and allows us to avoid the non-homogeneity of relevant identification equations. In order to consider the impact of gravity compensator that creates closed-loop chains, the conventional stiffness model is extended by including in it some configuration dependent elastostatic parameters, which are assumed to be constant for strictly serial robots. Corresponding methodology for calibration of the gravity compensator models is also proposed. The advantages of the developed calibration techniques are validated via experimental study, which deals with geometric and elastostatic calibration of a KUKA KR-270 industrial robot.

As robotic systems move from well-controlled settings to increasingly unstructured environments, they are required to operate in highly dynamic and cluttered scenarios. Finding an object, estimating its pose, and tracking its pose over time within such scenarios are challenging problems. Although various approaches have been developed to tackle these problems, the scope of objects addressed and the robustness of solutions remain limited. In this thesis, we target a robust object perception using visual sensory information, which spans from the traditional monocular camera to the more recently emerged RGB-D sensor, in unstructured environments. Toward this goal, we address four critical challenges to robust 6-DOF object pose estimation and tracking that current state-of-the-art approaches have, as yet, failed to solve. The first challenge is how to increase the scope of objects by allowing visual perception to handle both textured and textureless objects. A large number of 3D object models are widely available in online object model databases, and these object models provide significant prior information including geometric shapes and photometric appearances. We note that using both geometric and photometric attributes available from these models enables us to handle both textured and textureless objects. This thesis presents our efforts to broaden the spectrum of objects to be handled by combining geometric and photometric features. The second challenge is how to dependably estimate and track the pose of an object despite the clutter in backgrounds. Difficulties in object perception rise with the degree of clutter. Background clutter is likely to lead to false measurements, and false measurements tend to result in inaccurate pose estimates. To tackle significant clutter in backgrounds, we present two multiple pose hypotheses frameworks: a particle filtering framework for tracking and a voting framework for pose estimation. Handling of object discontinuities during tracking, such as severe occlusions, disappearances, and blurring, presents another important challenge. In an ideal scenario, a tracked object is visible throughout the entirety of tracking. However, when an object happens to be occluded by other objects or disappears due to the motions of the object or the camera, difficulties ensue. Because the continuous tracking of an object is critical to robotic manipulation, we propose to devise a method to measure tracking quality and to re-initialize tracking as necessary. The final challenge we address is performing these tasks within real-time constraints. Our particle filtering and voting frameworks, while time-consuming, are composed of repetitive, simple and independent computations. Inspired by that observation, we propose to run massively parallelized frameworks on a GPU for those robotic perception tasks which must operate within strict time constraints.