Grasping can be a complicated process for robotics due to the replication of human fine motor skills and typically high degrees of freedom in robotic hands. Robotic hands that are underactuated provide a method by which grasps can be executed without the onerous task of calculating every fingertip placement. The general shape configuration modes available to underactuated hands lend themselves well to an approach of grasping by shape primitives, and especially so when applied to gloveboxes in the nuclear domain due to the finite number of objects anticipated and the safe assumption that objects in the set are rigid. Thus, the object set found in a glovebox can be categorized as a small set of primitives such as cylinders, cubes, and bowls/hemispheres, etc. These same assumptions can also be leveraged for reliable identification and pose estimation within a glovebox. This effort develops and simulates a simple, but robust and effective grasp planning algorithm for a 7DOF industrial robot and three fingered dexterous, but underactuated robotic hand. The proposed grasping algorithm creates a grasp by generating a vector to the object from the base of the robot and manipulating that vector to be in a suitable starting location for a grasp. The grasp preshapes are selected to match shape primitives and are built-in to the Robotiq gripper used for algorithm demonstration purposes. If a grasp is found to be unsuitable via an inverse kinematics solution check, the algorithm procedurally generates additional grasps to try based on object geometry until a solution can be found or all possibilities are exhausted. The algorithm was tested and found capable of generating valid grasps for visually identified objects, and can recalculate grasps if one is found to be incompatible with the current kinematics of the robotic arm. / text

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduaçõa em Ciência da Computação. / Made available in DSpace on 2012-10-23T05:34:18Z (GMT). No. of bitstreams: 0Bitstream added on 2013-07-16T20:06:07Z : No. of bitstreams: 1 249954.pdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Este trabalho apresenta um conjunto de princípios que, se aplicados para a definição de contratos de operações de sistema, possibilitam a geração automática de diagramas de comunicação (UML). Os diagramas assim gerados podem ser usados também para geração automática de código. O mecanismo que gera os diagramas de comunicação é um sistema de busca, o qual foi projetado para encontrar diagramas que realizam um contrato de acordo com os padrões de projeto GRASP - General Responsibility Assignment Software Patterns. Os contratos são escritos em uma linguagem que consiste em uma variação da OCL (Object Constraint Language) adaptada para representar explicitamente os cinco tipos de pós-condições semânticas possíveis em modelos orientados a objetos. Apesar de seu considerável poder de geração, o mecanismo de busca resume-se a um conjunto de apenas quatro regras. O sistema foi implementado e testado em diversos contratos típicos de sistemas de informação, produzindo em todos os casos os resultados almejados. Estes resultados podem ser generalizados também para contratos mais complexos.

This thesis presents contributions to applied robotic control and manipulation in the areas of motion algorithm design, hardware, and software robotic system design. Mobile robotic systems are widely used in several applications. Control of such systems poses many challenges caused by system modeling uncertainty. Complex physics phenomena and environmental effects are usually neglected to simplify analysis and control design. In motion planning, this thesis introduces an algorithm for navigation learning in mobile robots that aims to reduce the effect of modeling uncertainties on control performance. Starting from an initial feasible state and input trajectories, the objective is to reduce navigation time through iterative trials. A nominal model of the actual system and the experimental system output are used to update the control input in every iteration for incremental improvement. The navigation problem is formulated as an optimal control problem that is solved after each trial to generate a vector of input deviations for the next trial. The formulation of the approach, simulation, and experimental results shows the effectiveness of the presented method. The design part focuses on developing hardware and software systems for manipulation and aerial robots. A software tool for automated generation of multirotor simulation models is developed utilizing CAD software API and Matlab. In the area of human-robot interaction, a human-supervised UAV inspection system has been developed and tested. The UAV is guided by a human operator using a handheld laser pointing device that is designed and fabricated in-house. In the field of robotic manipulation, a novel gripper mechanism is designed and implemented. The proposed mechanism targets applications where a grasped object lies in areas with limited surrounding clearance and where external torques affect the grasped object. This design was implemented on a mobile manipulation platform and tested during an international robotics competition.

Robotic grasping and manipulation of three-dimensional deformable objects is a complex task that currently does not have robust and flexible solutions. Deformable objects include a wide variety of elastic and inelastic objects that change size and shape during manipulation. The development of adaptable methods for grasping and autonomously controlling the shape of three-dimensional deformable objects will benefit many commercial applications, including shaping parts for assembly in manufacturing, manipulating food for packaging and controlling tissues during robotic surgery. Controlling a deformable object to a desired shape requires first choosing contact points on the object's surface. Next, the robotic hand is positioned in the correct position and orientation to grasp and deform the object. After deformation, the object is assessed to evaluate the quality of the shape control procedure. In many cases, this process is completed without knowing the object's properties or behaviour before deformation. This work proposes and implements the framework for a robotic arm and hand system to control the shape of a previously unseen deformable object autonomously. Significant original contributions are made in developing an original algorithm to plan contact points on a three-dimensional object for grasping and shape control. This research uses a novel object representation to reduce the dimensionality of the deformable object manipulation problem. A path planning algorithm guides the robot arm to the optimal valid grasp pose to deform the object at the determined contact points. Additional contributions include developing a multi-view assessment strategy to determine the quality of the deformation towards the desired shape. The system completes the objectives using depth and colour images captured from a single point of view to locate and identify a previously unseen three-dimensional object within a robotic workspace. After estimating the unknown object's geometry, initial grasp contact points are planned to control the object to the desired shape. The grasp points are used to plan and execute a collision-free trajectory for the robot manipulator to place the robotic hand in the optimal position and orientation to grasp and deform the object. After the deformation is complete, the object is moved to a variety of assessment positions to determine the success of the shape control procedure. The system is validated experimentally on a variety of deformable three-dimensional objects.

O trabalho apresentado nesta dissertação é referente ao estudo da evacuação de pessoas, mais especificamente, a evacuação predial faseada. O objetivo é determinar, para instâncias de até 25 andares, os instantes de liberação de cada grupo de pessoas, a fim de minimizar o tempo total de evacuação do edifício. No entanto, a determinação destes instantes deve considerar o risco ao qual os diferentes grupos estão submetidos, priorizando a evacuação do andar afetado. Além disso, os conflitos de diferentes grupos por espaço nas rotas de evacuação também devem ser evitados, já que, são nessas situações que acontecem grande parte dos acidentes. Para atingir tal objetivo, foi elaborado um modelo matemático de programação linear inteira. Devido à alta complexidade do modelo, fez-se necessária a aplicação de métodos heurísticos para a obtenção de soluções. Dessa maneira, foram desenvolvidas uma heurística de busca baseada em GRASP e uma heurística lagrangeana. Apesar da heurística lagrangeana atestar a qualidade da solução (a partir da comparação do resultado obtido com o limitante inferior), a heurística de busca mostrou-se mais adequada para o problema, pois forneceu resultados de qualidade com pouco esforço computacional. / This dissertation studies the evacuation of people, more specifically, building phased evacuation. The objective of this study is to determine, for buildings of up to 25 floors, in which instants each group of people has to be released, in order to minimize the total evacuation time. Furthermore, the determination of these instants has to consider the risk to which each group of people is submitted, thus the affected floor has to be the first group to be released. In addition, conflicts for space between groups should be avoided, since such situations increase the occurrences of accidents. To achieve this goal, an integer linear programming model was designed. Due to the high complexity of the model, it was necessary to apply heuristics to obtain solutions for some instances. Therefore, a search heuristic based on GRASP and a lagrangian heuristic were developed. Despite the fact that the lagrangian heuristic attests to the quality of the solution (when it is compared to the lower bound), the search heuristic was considered more suitable for this problem because it provided quality results with lower computational efforts.

Grasp should be selected intelligently to fulfill different stability properties and manipulative requirements. Currently, most grasping approaches consider only pick-and-place tasks without any physical interaction with other objects or the environment, which are common in an industry setting with limited uncertainty. When robots move to our daily-living environment and perform a broad range of tasks in an unstructured environment, all sorts of physical interactions will occur, which will result in random physical interactive wrenches: forces and torques on the tool. In addition, for a tool to perform a required task, certain motions need to occur. We call it "functional tool motion," which represents the innate function of the tool and the nature of the task. Grasping with a robotic hand gives flexibility in "mounting" the tool onto the robotic arm - a different grasp will connect the tool to the robotic arm with a different hand posture, then the inverse kinematics approach will result in a different joint motion of the arm in order to achieve the same functional tool motion. Thus, the grasp and the functional tool motion decide the manipulator's motion, as well as the effort to achieve the motion. Therefore, we propose to establish two objectives to serve the purpose of a grasp: the grasp should maintain a firm grip and withstand interactive wrenches on the tool during the task; and the grasp should enable the manipulator to carry out the task most efficiently with little motion effort, and then search for a grasp to optimize both objectives. For this purpose, two grasp criteria are presented to evaluate the grasp: the task wrench coverage criterion and the task motion effort criterion. The two grasp criteria are used as objective functions to search for the optimal grasp for grasp planning. To reduce the computational complexity of the search in high-dimensional robotic hand configuration space, we propose a novel grasp synthesis approach that integrates two human grasp strategies - grasp type, and thumb placement (position and direction) - into grasp planning. The grasping strategies abstracted from humans should meet two important criteria: they should reflect the demonstrator's intention, and they should be general enough to be used by various robotic hand models. Different abstractions of human grasp constrain the grasp synthesis and narrow down the solutions of grasp generation to different levels. If a strict constraint is imposed, such as defining all contact points of the fingers on the object, the strategy loses flexibility and becomes rarely achievable for a robotic hand with a different kinematic model. Thus, the choice of grasp strategies should balance the learned constraints and required flexibility to accommodate the difference between a human hand and a robotic hand. The human strategies of grasp type and thumb placement have such a balance while conveying important human intents to the robotic grasping. The proposed approach has been thoroughly evaluated both in simulation and on a real robotic system for multiple objects that would be encountered in daily living.

Submitted by Lara Oliveira (lara@ufersa.edu.br) on 2017-04-17T22:15:28Z No. of bitstreams: 1 AlexsandroTSS_DISSERT.pdf: 2805904 bytes, checksum: d89eac5a3d1bbff746e28effc0f94ba8 (MD5) / Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-04-26T12:14:12Z (GMT) No. of bitstreams: 1 AlexsandroTSS_DISSERT.pdf: 2805904 bytes, checksum: d89eac5a3d1bbff746e28effc0f94ba8 (MD5) / Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-04-26T12:16:44Z (GMT) No. of bitstreams: 1 AlexsandroTSS_DISSERT.pdf: 2805904 bytes, checksum: d89eac5a3d1bbff746e28effc0f94ba8 (MD5) / Made available in DSpace on 2017-04-26T12:19:14Z (GMT). No. of bitstreams: 1 AlexsandroTSS_DISSERT.pdf: 2805904 bytes, checksum: d89eac5a3d1bbff746e28effc0f94ba8 (MD5) Previous issue date: 2016-07-20 / The use of metaheuristics for solving combinatorial optimization problems belong to NP-Hard class is becoming increasingly common, and second Temponi (2007 apud RIBEIRO, 1996) a metaheurist should be modeled according to the problem she was designed to solve. This most often requires many changes when you have to apply the same metaheuristic to various types of combinatorial optimization problems. In this work we propose a framework for use of a hybrid metaheuristic proposed by Almeida (2014) who used the GRASP Reactive along with a reinforcement learning technique (called GR-learning). Specifically, the Q-learning algorithm that was used to learn over which the iterations value for the parameter α (alpha) used during the construction phase of GRASP. The GR-Learning was used to solve the problem of p-centers applied to Public Security in the city of Mossoró/RN. To validate the effectiveness of the framework proposed it was used to solve two classical problems of combinatorial optimi-zation: The Hub Location Problem (HLP), and the Cutting Stock Problem (CSP). To validate the results obtained we used instances with results known in the literature and in addition has created an instance with data from the Brazilian airline industry. The results showed that the proposed framework was quite competitive when compared to other results of different algo-rithms known in the literature as got great value in almost all instances of HLP as well as new values (better than those obtained with other algorithms known in the literature) for some ins-tances of CSP / A utilização de metaheurísticas para resolução de problemas de otimização combinatória per-tencentes à classe NP-Difícil vem se tornando cada vez mais comum, e segundo Temponi (2007 apud RIBEIRO, 1996) uma metaheurística deve ser modelada de acordo com o proble-ma que ela foi projetada para resolver. Isto na maioria vezes requer muitas alterações quando se tem que aplicar uma mesma metaheurística a diversos tipos de problemas de otimização combinatória. Neste trabalho foi proposto um framework para utilização de uma metaheurísti-ca híbrida proposta por Almeida (2014) que utilizou a metaheurística GRASP Reativo junta-mente com uma técnica de aprendizagem por reforço (denominada GR-Learning). Especifi-camente, o algoritmo Q-learning, que foi utilizado para aprender com o passar das iterações qual valor para o parâmetro α (alfa) utilizar durante a fase de construção da GRASP. O GR-Learning foi utilizado para resolver o problema dos p-Centros aplicado a Segurança Pública na Cidade de Mossoró/RN. Para validar a eficácia do framework proposto o mesmo foi utili-zado para resolver dois problemas clássicos de otimização combinatória: O Problema de Lo-calização de Hubs (do inglês Hub Location Problem - HLP) e o Problema de Corte e Estoque – PCE (do inglês Cutting Stock Problem - CSP). Para validação dos resultados obtidos foram utilizadas instâncias com resultados já conhecidos na literatura e adicionalmente foi criada uma instância com dados do setor aeroviário Brasileiro. Os resultados obtidos mostraram que o framework proposto foi bastante competitivo quando comparado a outros resultados de di-versos algoritmos já conhecidos na literatura, pois obteve o valor ótimo em quase todas as instâncias do HLP como também novos valores (melhores que os obtidos com outros algorit-mos já conhecido na literatura) para algumas instâncias do CSP / 2017-04-17

Made available in DSpace on 2014-06-11T19:22:33Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-02-25Bitstream added on 2014-06-13T18:08:31Z : No. of bitstreams: 1 mathiasneto_wp_me_ilha.pdf: 1434881 bytes, checksum: 53cd385d84e1308e7b8ae91adeb1e5e7 (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Neste trabalho propõe-se um algoritmo para a restauração de redes de distribuição de energia elétrica em tempo real baseado na meta-heurística GRASP (Greed Randomized Adaptative Search Procedure) considerando a inserção de geradores distribuídos. O problema é modelado como não linear inteiro misto e considera os dois principais objetivos da restauração de redes de distribuição: minimizar número de consumidores sem fornecimento de energia elétrica e o número de chaveamentos. O algoritmo desenvolvido a partir da metodologia proposta foi implementado em linguagem de programação C++ e testado em um sistema real de distribuição de grande porte. A partir dos resultados obtidos verificou-se o bom desempenho do algoritmo, tanto em termos de robustez quanto em desempenho computacional, ao encontrar um conjunto de soluções factíveis e de boa qualidade, dentro de um tempo computacional considerado adequado para o problema de restauração / This work proposes a methodology to distribution power system restoration considering distributed generators installed on the system. The methodology is based on GRASP (Greed Randomized Adaptive Search Procedure) metaheuristic and the restoration problem is established as nonlinear mixed-integer taking account two mainly goals: minimizing both the number of consumers without supply and the number of switching. The algorithm based on proposed methodology is implemented in C++ programming language and tested using a bulk real-life distribution power system. The results show the methodology is able to provide a set of feasible and good quality solutions in a suitable time for the restoration problem

O trabalho apresentado nesta dissertação é referente ao estudo da evacuação de pessoas, mais especificamente, a evacuação predial faseada. O objetivo é determinar, para instâncias de até 25 andares, os instantes de liberação de cada grupo de pessoas, a fim de minimizar o tempo total de evacuação do edifício. No entanto, a determinação destes instantes deve considerar o risco ao qual os diferentes grupos estão submetidos, priorizando a evacuação do andar afetado. Além disso, os conflitos de diferentes grupos por espaço nas rotas de evacuação também devem ser evitados, já que, são nessas situações que acontecem grande parte dos acidentes. Para atingir tal objetivo, foi elaborado um modelo matemático de programação linear inteira. Devido à alta complexidade do modelo, fez-se necessária a aplicação de métodos heurísticos para a obtenção de soluções. Dessa maneira, foram desenvolvidas uma heurística de busca baseada em GRASP e uma heurística lagrangeana. Apesar da heurística lagrangeana atestar a qualidade da solução (a partir da comparação do resultado obtido com o limitante inferior), a heurística de busca mostrou-se mais adequada para o problema, pois forneceu resultados de qualidade com pouco esforço computacional. / This dissertation studies the evacuation of people, more specifically, building phased evacuation. The objective of this study is to determine, for buildings of up to 25 floors, in which instants each group of people has to be released, in order to minimize the total evacuation time. Furthermore, the determination of these instants has to consider the risk to which each group of people is submitted, thus the affected floor has to be the first group to be released. In addition, conflicts for space between groups should be avoided, since such situations increase the occurrences of accidents. To achieve this goal, an integer linear programming model was designed. Due to the high complexity of the model, it was necessary to apply heuristics to obtain solutions for some instances. Therefore, a search heuristic based on GRASP and a lagrangian heuristic were developed. Despite the fact that the lagrangian heuristic attests to the quality of the solution (when it is compared to the lower bound), the search heuristic was considered more suitable for this problem because it provided quality results with lower computational efforts.

The main objective of this work is to propose optimization methods of the production to a medium size market foundry industry. Taking into consideration the peculiarities of the enterprise used as case study, on the contrary of many other works in this area, the present research is focused in the production programming which is based in the macharia ( it is a mold made of sand which serves to give shape to the final piece) and molding machines programming. The kilns programming do not represent a delay in the productive process which has been studied, however, their capacity is taken into consideration during the production of the optimization methods. The proposed model considers the programming of tasks in parallel machines with families set up dependent of the sequence. In order to solve the problem it is used a meta-heurística GRASP. The computing results show that it is significantly possible to improve the procedure of the production programming nowadays used in the foundry industry case study. / O presente trabalho tem por objetivo propor métodos de otimização da produção para uma fundição de mercado de médio porte. Dada as peculiaridades da empresa utilizada como estudo de caso, diferentemente de outros trabalhos nesta área, a presente pesquisa enfoca a programação da produção baseada na programação das máquinas da macharia e da moldagem. A programação dos fornos não representa gargalo no processo produtivo em estudo, no entanto, a capacidade dos mesmos é levada em conta no momento da confecção dos métodos de otimização. O modelo proposto considera a programação de tarefas em máquinas paralelas com famílias de setup dependente da seqüência. Para resolver o problema assim definido é utilizada uma meta-heurística GRASP. Os resultados computacionais demonstram que é possível melhorar significativamente o procedimento de programação da produção utilizado atualmente na fundição estudo de caso.