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In this thesis the subject innovation and the change of meaning is in focus. The purpose of the study is to present a new dimension of innovation as a change of meaning together with the cases we’ve studied. It is discussed throughout the article if theories of perception and association can affect the organization and its ability to create meaning-changing innovations. The industrial robotics is a market in need of, perhaps, if not other markets but of finding new ground that results in the change of meaning. What happens when you stand at the intersection of main areas in the field of innovation? Is it possible that meaningful change can be found here, amongst radical innovation and industrial robotic arms and it’s technology? Our methods were interviews and prior research complementing the cases we’ve presented. We want to show how meaning can change various dimensions. Together with a perceptual theory and an innovation theory we’ve found out that meaning and innovation can go hand in hand.

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Made available in DSpace on 2014-06-11T19:34:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-05Bitstream added on 2014-06-13T20:06:00Z : No. of bitstreams: 1 nunes_lenp_dr_guara.pdf: 1711475 bytes, checksum: 1ea89d3a534a0a1530a9ef0a0ba7cb3e (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho trata da geração e otimização de trajetórias de um manipulador robótico planar (2D) de três graus de liberdade, num ambiente livre de obstáculos. Visto que a cinemática inversa de braços robóticos é um problema complexo que, em geral, geram múltiplas soluções, otimizam-se, aqui, estas soluções através de algoritmos genéticos (AGs). A função de avaliação do AG tem caráter multi-objetivo, de forma a minimizar os deslocamentos angulares e obter de forma precisa a posição da garra, usando funções desenvolvidas para o ambiente Matlab, tais como, GAOT e PLANMANT, devido a sua facilidade de programação e geração de gráficos. A seguir, foram obtidos resultados através de programa desenvolvido em linguagem C, utilizando a biblioteca GAUL, e tem-se avaliado o desempenho computacional de processamento. E finalmente, para a validação experimental deste estudo, tem-se implementado este procedimento em um manipulador robótico Robix RCS-6 de configuração similar ao modelo simulado. Os resultados mostram que o método implementado é eficiente, computacionalmente rápido e viável em aplicações reais. / This work treats of the generation and optimization of trajectories for a planar robotic manipulator (2D) of three degrees of freedom, in free environment obstacles. Since the inverse kinematics of robotic arms are a complex problem that, generally, generate multiple solutions, here are optimized these solutions through genetic algorithms (AGs). The evaluation function of the AG has multi-objective character which minimize the angular displacements and the positional errors, being used functions developed for the Matlab environment, such as, GAOT and PLANMANT, due its compliance of programming and graphics generation. Immediately, results were obtained through program developed in language C, using the GAUL library. The computational processing performance has been evaluated. And finally, for the experimental validation of this study, has been implemented this procedure in a robotic manipulator Robix RCS-6 of similar configuration to the simulated model. The results show that the implemented method is efficient, and computationally fast and viable in real applications. KEYWORDS: Robotic manipulator, Optimal trajectory, Inverse kinematics, Genetic algorithm.

Metallic robotic arms, or manipulators, currently dominate automated industrial operations, but due to their intrinsic weight, have limited usefulness for large-scale applications in terms of precision, speed, and repeatability. This thesis focuses on exploring the feasibility of using polymeric composite materials for the construction of long-reach robotic arms. Different manipulator layouts were investigated and an ideal design was selected for a robotic arm that has a 5 [m] reach, 50 [kg] payload, and is intended to operate on large objects with complex curvature. The cross-sectional geometry of the links of the arm were analyzed for optimal stiffness- and strength-to-weight ratios that are capable of preserving high precision and repeatability under time-dependent external excitations. The results lead to a novel multi-segment link design and method of production. A proof-of-concept prototype of a two degrees-of-freedom (2-DOF) robotic arm with a reach of 1.75 [m] was developed. Both static and repeatability testing were performed for verification. The results indicated that the prototype robot main-arm constructed of carbon fiber-epoxy composite material provides good stiffness-to-weight and strength-to-weight ratios. Finite element analysis (FEA) was performed on a 3-D computer model of the arm. Successful verification led to the use of the 3-D model to define the dimensions of an industrial-sized robotic arm. The results obtained indicate high stiffness and minimal deflection while achieving a significant weight reduction when compared to commercial arms of the same size and capability.

Resumo: Este trabalho trata da geração e otimização de trajetórias de um manipulador robótico planar (2D) de três graus de liberdade, num ambiente livre de obstáculos. Visto que a cinemática inversa de braços robóticos é um problema complexo que, em geral, geram múltiplas soluções, otimizam-se, aqui, estas soluções através de algoritmos genéticos (AGs). A função de avaliação do AG tem caráter multi-objetivo, de forma a minimizar os deslocamentos angulares e obter de forma precisa a posição da garra, usando funções desenvolvidas para o ambiente Matlab, tais como, GAOT e PLANMANT, devido a sua facilidade de programação e geração de gráficos. A seguir, foram obtidos resultados através de programa desenvolvido em linguagem C, utilizando a biblioteca GAUL, e tem-se avaliado o desempenho computacional de processamento. E finalmente, para a validação experimental deste estudo, tem-se implementado este procedimento em um manipulador robótico Robix RCS-6 de configuração similar ao modelo simulado. Os resultados mostram que o método implementado é eficiente, computacionalmente rápido e viável em aplicações reais. / Abstract: This work treats of the generation and optimization of trajectories for a planar robotic manipulator (2D) of three degrees of freedom, in free environment obstacles. Since the inverse kinematics of robotic arms are a complex problem that, generally, generate multiple solutions, here are optimized these solutions through genetic algorithms (AGs). The evaluation function of the AG has multi-objective character which minimize the angular displacements and the positional errors, being used functions developed for the Matlab environment, such as, GAOT and PLANMANT, due its compliance of programming and graphics generation. Immediately, results were obtained through program developed in language C, using the GAUL library. The computational processing performance has been evaluated. And finally, for the experimental validation of this study, has been implemented this procedure in a robotic manipulator Robix RCS-6 of similar configuration to the simulated model. The results show that the implemented method is efficient, and computationally fast and viable in real applications. KEYWORDS: Robotic manipulator, Optimal trajectory, Inverse kinematics, Genetic algorithm. / Orientador: Victor Orlando Gamarra Rosado / Coorientador: Francisco José Grandinetti / Banca: Mauro Pedro Peres / Banca: Luiz Octavio Mattos dos Reis / Banca: José Rui Camargo / Banca: Carlos Alberto Chavez / Doutor

Σκοπός της παρούσας διπλωματικής εργασίας είναι η ανάπτυξη και ο έλεγχος ρομποτικού συστήματος για την επεξεργασία βωξίτη. Αφορά συγκεκριμένα το μηχανολογικό σχεδιασμό του συστήματος, την επιλογή εξοπλισμού, τον ηλεκτρολογικό σχεδιασμό, τον έλεγχο με χρήση προγραμματιζόμενου λογικού ελεγκτή (PLC) και τέλος την υλοποίηση εφαρμογής scada / The purpose of this thesis is the development and control of robotic system for processing bauxite. Concern in particular the mechanical system design, the choice of equipment, the electrical design, the control using programmable logic controller (PLC) and finally the creation of scada application.

This thesis presents the development of a collision avoidance system for human robot collaboration applications where a human shares its workspace with a robotic arm. A vision system is used to capture colour point clouds of the shared workspace in real-time. An easy-to-use calibration method is then developed to transform the point clouds to the robot’s coordinate frame. Algorithms for processing the transformed points to obtain models of the human and static obstacle(s), and a method used to model the robot, were developed next. The human is modelled by a plane in front of their torso, and any body parts or objects in the front of this plane are modelled by spheres. This model is more computationally efficient compared to the spheres-only modelling method. Methods for predicting the motions of the human’s arms, head and torso were also developed. Next, two predictive collision avoidance algorithms that account for the system dead time were developed. Five metrics were proposed for evaluating the collision avoidance and trajectory tracking performances of the algorithms. The 1st collision avoidance algorithm is an optimal algorithm, and the 2nd collision avoidance is a non-optimal algorithm. The robotic arm used in this research is an Elfin 5 industrial robot. Simulations of the robot avoiding a static obstacle using the 2nd algorithm demonstrated the necessity of using prediction whenever system dead time is present. Both algorithms were then simulated with a human model moving with a constant speed blocking the robot’s path. Based on the superior performance of the 1st algorithm in collision avoidance and trajectory tracking, it was selected for the rest of the collision avoidance experiments. Three real-time human robot collaboration scenarios requiring collision avoidance were studied experimentally. The experimental results demonstrate the consistent excellent collision avoidance and trajectory tracking performance of the 1st algorithm in all scenarios. The algorithm accelerates the robot to compensate for the time spent performing collision avoidance so that no productivity is lost, unlike many prior approaches. Its computational speed is also faster than other optimal collision avoidance algorithms for human-robot collaboration. / Thesis / Master of Applied Science (MASc) / People are having more and more interaction and collaboration with robots both in industry and at home. Sharing a workspace with a robot requires the robot to know where the person is, and to avoid contacting them while performing their tasks. In this research, a collision avoidance system for human-robot collaboration was developed to solve this problem. The vision system is developed to capture real-time colour and depth data of the robot and its surroundings. A software algorithm is proposed to model the person by geometric shapes using these data. Two more software algorithms are proposed to control the robotic arm. Both of them worked well when tested using a simulated industrial robotic arm with a significant time delay. The algorithm with the better performance was selected to be tested using the industrial robotic arm in real-time. The results show that the algorithm can consistently move the gripper of the robotic arm to its target location while simultaneously avoiding collisions with the person’s moving body in different human-robot collaboration scenarios.

Industrial robot programs are usually created with the programming language that the manufacturer provides. These languages are often limited to cover the common usages within the industry. However, when a more advanced program is needed, then third-party programs are often used to, e.g., locating objects using vision systems, applying correct force with force torque sensors, etc. Instead of using both the language of the robot and third-party programs to create more advanced programs, it is preferable to have one system that can fully control the robot. Such systems exist, e.g., Robot Operating System (ROS), Yet Another Robot Language (YARP), etc. These systems require more time to fully set up, but once they are set up supposedly they can be used for a lot of different applications and can be used on several industrial robots from different manufacturers. Currently, University of Skövde have robots from Universal Robots (UR) with several peripheral equipment which has limited control because the built-in language does not support it. Therefore, they need help with both investigating which robot system could be used and implementing that robot system. This thesis will prove the suitability of using ROS to control aforesaid hardware, fulfilling all the requirements. It will be also demonstrated the feasibility of ROS in the long-term, according to the future plans for this equipment in University of Skövde.

I industriella miljöer är det avgörande att säkerställa människors säkerhet runt robotarmar för att förhindra allvarliga skador vid olyckor. Denna studie syftar till att utveckla ett realtidssystem för fara-detektering som använder datorseende och prediktiva modeller för att förbättra säkerheten. Genom att kombinera YOLOv8-algoritmen för objektigenkänning med Kalmanfiltrering (KF) och Dead Reckoning (DR) kan systemet upptäcka människors närvaro och förutsäga rörelser för att minska risken för olyckor. Det första experimentet visar att KF presterar bättre än DR, särskilt vid linjära rörelser, med lägre medelabsolutfel (MAE) och medelkvadratfel (MSE). Det andra experimentet visar att integrationen av KF med YOLOv8 resulterar i högre precision, noggrannhet och balanserad noggrannhet, även om återkallning fortfarande behöver förbättras. Dessa resultat indikerar att kombinationen av datorseende och prediktiva modeller har betydande potential att förbättra människors säkerhet. Ytterligare forskning och tester i olika scenarier är dock nödvändiga innan implementering i verkliga miljöer. / In industrial environments, ensuring human safety around robotic arms is crucial to prevent severe injuries from accidents. This study aims to develop a real-time hazard detection system using computer vision and predictive modeling techniques to improve safety. By combining the YOLOv8 object detection algorithm with Kalman Filtering (KF) and Dead Reckoning (DR), the system can detect human presence and predict movements to reduce the risk of accidents. The first experiment shows that KF outperforms DR, especially in linear movements, with lower Mean Absolute Error (MAE) and Mean Squared Error (MSE). The second experiment demonstrates that integrating KF with YOLOv8 results in higher precision, accuracy, and balanced accuracy, although recall still needs improvement. These findings indicate that combining computer vision with predictive modeling has significant potential to enhance human safety. However, further research and testing in diverse scenarios are necessary before real-world deployment.