Gliders2d: Source Code Base for RoboCup 2D Soccer Simulation League

We describe Gliders2d, a base code release for Gliders, a soccer simulation team which won the RoboCup Soccer 2D Simulation League in 2016. We trace six evolutionary steps, each of which is encapsulated in a sequential change of the released code, from v1.1 to v1.6, starting from agent2d-3.1.1 (set as the baseline v1.0). These changes improve performance by adjusting the agents' stamina management, their pressing behaviour and the action-selection mechanism, as well as their positional choice in both attack and defense, and enabling riskier passes. The resultant behaviour, which is sufficiently generic to be applicable to physical robot teams, increases the players' mobility and achieves a better control of the field. The last presented version, Gliders2d-v1.6, approaches the strength of Gliders2013, and outperforms agent2d-3.1.1 by four goals per game on average. The sequential improvements demonstrate how the methodology of human-based evolutionary computation can markedly boost the overall performance with even a small number of controlled steps.Comment: 12 pages, 1 figure, Gliders2d code releas

Location and Position Determination Algorithm For Humanoid Soccer Robot

The algorithm of location and position determination was designed for humanoid soccer robot. The robots have to be able to control the ball effectively on the field of Indonesian Robot Soccer Competition which has a size of 900 cm x 600 cm. The algorithm of location and position determination uses parameters, such as the goalpost’s thickness, the compass value, and the robot’s head servo value. The goalpost’s thickness is detected using The Centre of Gravity method. The width of the goalpost detected is analyzed using the principles of camera geometry to determine the distance between the robot and the goalpost. The tangent value of head servo’s tilt angle is used to determine the distance between the robot and the ball. The distance between robot-goalpost and the distance between robot-ball are processed with the difference of head servo’s pan angle and compass value using trigonometric formulas to determine the coordinates of the robot and the ball in the Cartesian coordinates

Jogadas estudadas dinâmicas para a equipa CAMBADA

Mestrado em Engenharia Eletrónica e TelecomunicaçõesRobotics is an emergent branch of engineering that involves the conception, manufacture, and control of robots. It is a multidisciplinary field that combines electronics, design, computer science, artificial intelligence, mechanics and nanotechnology. Its evolution results in machines that are able to perform tasks with some level of complexity. Multi-agent systems is a researching topic within robotics, thus they allow the solving of higher complexity problems, through the execution of simple routines. Robotic soccer allows the study and development of robotics and multiagent systems, as the agents have to work together as a team, having in consideration most problems found in our quotidian, as for example adaptation to a highly dynamic environment as it is the one of a soccer game. CAMBADA is the robotic soccer team belonging to the group of research IRIS from IEETA, composed by teachers, researchers and students of the University of Aveiro, which annually has as main objective the participation in the RoboCup, in the Middle Size League. The purpose of this work is to improve the coordination in set pieces situations. This thesis introduces a new behavior and the adaptation of the already existing ones in the offensive situation, as well as the proposal of a new positioning method in defensive situations. The developed work was incorporated within the competition software of the robots. Which allows the presentation, in this dissertation, of the experimental results obtained, through simulation software as well as through the physical robots on the laboratory.A robótica é um ramo emergente da engenharia que envolve a concepção, fabrico e controlo de robôs. É uma área multidisciplinar que conjuga conhecimentos de mecânica, design, electrónica e computação, inteligência artificial e nanotecnologia. A sua evolução resulta em máquinas capazes de realizar tarefas com alguma complexidade. Sistemas multi-agente, são um dos temas de pesquisa dentro da robótica, pois permitem a realização de tarefas de maior complexidade, através da execução de rotinas simples. O futebol robótico permite o estudo e desenvolvimento de robótica e de sistemas multi-agente, uma vez que os agentes tem de trabalhar em equipa, tendo em consideração grande parte dos problemas que encontramos no nosso quotidiano, como por exemplo a adaptação a um ambiente extremamente dinâmico como o de um jogo de futebol. CAMBADA _e a equipa de futebol robótico pertencente ao grupo de investigação IRIS, do IEETA, constituída por docentes, investigadores e alunos da Universidade de Aveiro, que anualmente tem como principal objetivo a participação no RoboCup na Middle Size League. Este trabalho tem como principal objectivo melhorar a coordenação da equipa em situações de bola parada. Esta tese introduz um novo comportamento e a adaptação dos já existentes para situações ofensivas, assim como propõe um novo método de posicionamento a ser usado em situações defensivas. O trabalho desenvolvido foi incorporado no software de competição dos robôs, o que permite nesta dissertação apresentar resultados experimentais obtidos através de simulação e de testes efetuados nos robôs em laboratório

Abstracting Multidimensional Concepts for Multilevel Decision Making in Multirobot Systems

Multirobot control architectures often require robotic tasks to be well defined before allocation. In complex missions, it is often difficult to decompose an objective into a set of well defined tasks; human operators generate a simplified representation based on experience and estimation. The result is a set of robot roles, which are not best suited to accomplishing those objectives. This thesis presents an alternative approach to generating multirobot control algorithms using task abstraction. By carefully analysing data recorded from similar systems a multidimensional and multilevel representation of the mission can be abstracted, which can be subsequently converted into a robotic controller. This work, which focuses on the control of a team of robots to play the complex game of football, is divided into three sections: In the first section we investigate the use of spatial structures in team games. Experimental results show that cooperative teams beat groups of individuals when competing for space and that controlling space is important in the game of robot football. In the second section, we generate a multilevel representation of robot football based on spatial structures measured in recorded matches. By differentiating between spatial configurations appearing in desirable and undesirable situations, we can abstract a strategy composed of the more desirable structures. In the third section, five partial strategies are generated, based on the abstracted structures, and a suitable controller is devised. A set of experiments shows the success of the method in reproducing those key structures in a multirobot system. Finally, we compile our methods into a formal architecture for task abstraction and control. The thesis concludes that generating multirobot control algorithms using task abstraction is appropriate for problems which are complex, weakly-defined, multilevel, dynamic, competitive, unpredictable, and which display emergent properties