Este trabalho apresenta o desenvolvimento de um modelo simplificado dos membros inferiores de um robô bípede, composto basicamente por uma cintura, dois fêmures, duas tíbias e dois pés. A estrutura mecânica do modelo em questão, possui seis graus de liberdade e tem as dimensões aproximadas de um ser humano de estrutura mediana. Seu sistema de controle e de geração de trajetórias é desenvolvido utilizando funcionalidades disponíveis no Robot Operating System (ROS), porém ao contrário da maioria dos controladores existentes no ROS, este projeto propõe implementar um pacote contendo um controlador multivariável (multi-input, multi-output (MIMO)), utilizando a técnica de controle por torque calculado. Para a geração de trajetórias das pernas do robô, implementam-se três tipos diferentes de geração, a interpolação linear, cubica e de quinto grau. Para os testes de validação do sistema de controle e de geração de trajetórias utiliza-se o simulador Gazebo. / This work presents the development of a simplified model of a biped robot’s lower limbs, composed basically by the waist, two femurs, two tibia and two feet. The model’s mechanical structure has six degree of freedom and its dimensions are comparable to a human being’s body. Its control and trajectory generation systems are developed making use of some features available in the Robot Operation System (ROS) tool. However, contrary to most of the controllers offered by ROS, this project suggests the implementation of a new package, including a MIMO (multi-input multi-output) controller, making use of the calculated torque technique. As for the trajectory generation system, three different methodologies are applied of the interpolation: linear, cubic and polynomial quintic. To validate both control and trajectory generation systems, the Gazebo simulator is used.

Este trabalho apresenta o desenvolvimento de um modelo simplificado dos membros inferiores de um robô bípede, composto basicamente por uma cintura, dois fêmures, duas tíbias e dois pés. A estrutura mecânica do modelo em questão, possui seis graus de liberdade e tem as dimensões aproximadas de um ser humano de estrutura mediana. Seu sistema de controle e de geração de trajetórias é desenvolvido utilizando funcionalidades disponíveis no Robot Operating System (ROS), porém ao contrário da maioria dos controladores existentes no ROS, este projeto propõe implementar um pacote contendo um controlador multivariável (multi-input, multi-output (MIMO)), utilizando a técnica de controle por torque calculado. Para a geração de trajetórias das pernas do robô, implementam-se três tipos diferentes de geração, a interpolação linear, cubica e de quinto grau. Para os testes de validação do sistema de controle e de geração de trajetórias utiliza-se o simulador Gazebo. / This work presents the development of a simplified model of a biped robot’s lower limbs, composed basically by the waist, two femurs, two tibia and two feet. The model’s mechanical structure has six degree of freedom and its dimensions are comparable to a human being’s body. Its control and trajectory generation systems are developed making use of some features available in the Robot Operation System (ROS) tool. However, contrary to most of the controllers offered by ROS, this project suggests the implementation of a new package, including a MIMO (multi-input multi-output) controller, making use of the calculated torque technique. As for the trajectory generation system, three different methodologies are applied of the interpolation: linear, cubic and polynomial quintic. To validate both control and trajectory generation systems, the Gazebo simulator is used.

Este trabalho apresenta o desenvolvimento de um modelo simplificado dos membros inferiores de um robô bípede, composto basicamente por uma cintura, dois fêmures, duas tíbias e dois pés. A estrutura mecânica do modelo em questão, possui seis graus de liberdade e tem as dimensões aproximadas de um ser humano de estrutura mediana. Seu sistema de controle e de geração de trajetórias é desenvolvido utilizando funcionalidades disponíveis no Robot Operating System (ROS), porém ao contrário da maioria dos controladores existentes no ROS, este projeto propõe implementar um pacote contendo um controlador multivariável (multi-input, multi-output (MIMO)), utilizando a técnica de controle por torque calculado. Para a geração de trajetórias das pernas do robô, implementam-se três tipos diferentes de geração, a interpolação linear, cubica e de quinto grau. Para os testes de validação do sistema de controle e de geração de trajetórias utiliza-se o simulador Gazebo. / This work presents the development of a simplified model of a biped robot’s lower limbs, composed basically by the waist, two femurs, two tibia and two feet. The model’s mechanical structure has six degree of freedom and its dimensions are comparable to a human being’s body. Its control and trajectory generation systems are developed making use of some features available in the Robot Operation System (ROS) tool. However, contrary to most of the controllers offered by ROS, this project suggests the implementation of a new package, including a MIMO (multi-input multi-output) controller, making use of the calculated torque technique. As for the trajectory generation system, three different methodologies are applied of the interpolation: linear, cubic and polynomial quintic. To validate both control and trajectory generation systems, the Gazebo simulator is used.

A mobile robot needs to know its pose (position and orientation) in order to navigate and perform useful tasks. The problem of determining this pose with respect to a global or local frame is called localisation, and is a key component in providing autonomy to mobile robots. Thus, localisation answers the question Where am I? from the robot’s perspective. Localisation involving a single robot is a widely explored and documented problem in mobile robotics. The basic idea behind most documented localisation techniques involves the optimum combination of noisy and uncertain information that comes from various robot’s sensors. However, many complex robotic applications require multiple robots to work together and share information among themselves in order to successfully and efficiently accomplish certain tasks. This leads to research in collaborative localisation involving multiple robots. Several studies have shown that when multiple robots collaboratively localise themselves, the resulting accuracy in their estimated positions and orientations outperforms that of a single robot, especially in scenarios where robots do not have access to information about their surrounding environment. This thesis presents the main theme of most of the existing collaborative, multi-robot localisation solutions, and proposes an alternative or complementary solution to some of the existing challenges in multirobot localisation. Specifically, in this thesis, a heuristically tuned Extended Kalman Filter is proposed to localise a group of mobile robots. Simulations show that when certain conditions are met, the proposed tuning method significantly improves the accuracy and reliability of poses estimated by the Extended Kalman Filter. Real world experiments performed on custom-made robotic platforms validate the simulation results.

No description available.

In this paper I describe a motion planning technique for intelligent ground vehicles. The technique is an implementation of a path selection algorithm based on fuzzy inference. The approach extends on the motion planning algorithm known as driving with tentacles. The selection of the tentacle (a drivable path) to follow relies on the calculation of a weighted cost function for each tentacle in the current speed set, and depends on variables such as the distance to the desired position, speed, and the closeness of a tentacle to any obstacles. A Matlab simulation and the practical implementation of the fuzzy inference rule on a Clearpath Husky robot within the Robot Operating System (ROS) framework are provided.

Based on analysis of human-human interactions, we have developed an initial model of engagement for human-robot interaction which includes the concept of connection events, consisting of: directed gaze, mutual facial gaze, conversational adjacency pairs, and backchannels. We implemented the model in the open source Robot Operating System and conducted a human-robot interaction experiment to evaluate it.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-07-25T17:21:34Z No. of bitstreams: 1 RaphaelSantos.pdf: 3718930 bytes, checksum: df335fd5562e8156000972c282fe9724 (MD5) / Made available in DSpace on 2017-07-25T17:21:34Z (GMT). No. of bitstreams: 1 RaphaelSantos.pdf: 3718930 bytes, checksum: df335fd5562e8156000972c282fe9724 (MD5) Previous issue date: 2016-08-17 / Autonomous exploration, in robotics, can be defined as the act of moving into an unknown environment, at priori, while building up a map of the environment. A great deal of literature describes several problems that are relate to the strategy exploration: perception, location, trajectory control and mapping. This work aims to present an autonomous exploration algorithm based on metaheuristics. Therefore, the problem of autonomous exploration of mobile robots is formulated as an optimization problem, providing data for metaheuristics that are able to search points in the space of solutions that represent positions on the map under construction that best meet the objectives of the exploration. Metaheuristics are approximate methods that guarantee sufficiently good solutions to optimization problems. The proposal was implemented and incorporated as an optimization module in a simultaneous location and mapping system that was run on the Robot Operating System environment and proved to be able to guide a simulated robot without human intervention. Two optimization metaheuristics were implemented to guide target to simulated robot: Genetic Algorithm and Firefly Algorithm. Both algorithms have achieved good results, however the second one was able to guide robot by best trajectories. / Exploração autônoma, em robótica, pode ser definida como o ato de mover-se em um ambiente, a princípio desconhecido, enquanto constrói-se um mapa deste ambiente. Uma grande parte da literatura relata vários problemas que se relacionam com a estratégia de exploração: percepção, localização, trajetória, controle e mapeamento. Este trabalho visa apresentar um algoritmo de exploração autonoma baseado em metaheurísticas. Para tanto, o problema de exploração autônoma de robôs móveis é formulado como um problema de otimização, fornecendo dados para que metaheurísticas sejam capazes de buscar pontos no espaço de soluções que representam posições no mapa em construção que melhor satisfaçam os objetivos da exploração. Metaheuristicas são metodos aproximados que garantem soluções suficientemente boas para problemas de otimização. A proposta foi implementada e incorporada como um módulo de otimização em um sistema de localização e mapeamento simultâneos que foi executado em ambiente Robot Operating System e mostrou-se capaz de guiar um robô simulado sem intervenção humana. As metaheurísticas usadas foram o Algoritmo Genético e o Algoritmo de Vagalumes. Ambos os algoritmos obtiveram bons resultados, no entanto o Algoritmo de Vagalumes guiou o robô por trajetórias melhores.

This thesis presents the design and development of a unique omni-directional platform known as the Omnibot which was built in the Mechatronic and Robotic Systems Laboratory at UOIT. The Omnibot's layout is novel because its drive axes do not intersect with the geometric center of the body, which is typical for omni-directional platforms using segmented omni-directional wheels. This design enables the center of mass to be lower in the design and increases the stability. A suspension system was designed for each of the four wheels to limit vibrations and to ensure contact between the wheels and operating surface. The Omnibot was built to modularly support many systems, including a robot arm, without altering the mechanical design of the frame. Two control modes were developed: local and global. Commands to drive the Omnibot can be received from either a joystick that can be directly interfaced with the controller or with commands that are sent from other systems that are either on or o of the Omnibot. Both control modes require encoder feedback to ensure commanded velocities are being executed as specified. Global control requires feedback from an indoor localization system to determine the Omnibot's pose. Early implementation of the localization system is discussed. An open source robotics software, known as Robot Operating System (ROS) was selected for implementation of the Omnibot systems. ROS serves as a middleware which allows components, such as the localization system and remote desktop, to communicate with each other through a decoupled messaging system. ROS is modular and exible, allowing for easy adaptation of future components. Test results of the Omnibot in operation are presented.

Localization and mapping are two of the most central tasks when it comes to autonomous robots. It has often been performed using expensive, accurate sensors but the fast development of consumer electronics has made similar sensors available at a more affordable price. In this master thesis a TurtleBot, robot and a Microsoft Kinect, camera are used to perform Simultaneous Localization And Mapping, SLAM. The thesis presents modifications to an already existing open source SLAM algorithm. The original algorithm, based on visual odometry, is extended so that it can also make use of measurements from wheel odometry and asingle axis gyro. Measurements are fused using an Extended Kalman Filter, EKF, operating in a multirate fashion. Both the SLAM algorithm and the EKF are implemented in C++ using the framework Robot Operating System, ROS. The implementation is evaluated on two different data sets. One set is recorded in an ordinary office room which constitutes an environment with many landmarks. The other set is recorded in a conference room where one of the walls is flat and white. This gives a partially sparse featured environment. The result by providing additional sensor information is a more robust algorithm. Periods without credible visual information does not make the algorithm lose its track and the algorithm can thus be used in a larger variety of environments including such where the possibility to extract landmarks is low. The result also shows that the visual odometry can cancel out drift introduced by wheel odometry and gyro sensors.