Synthesized cooperative strategies for intelligent multi-robots in a real-time distributed environment : a thesis presented in partial fulfillment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, New Zealand

In the robot soccer domain, real-time response usually curtails the development of more complex Al-based game strategies, path-planning and team cooperation between intelligent agents. In light of this problem, distributing computationally intensive algorithms between several machines to control, coordinate and dynamically assign roles to a team of robots, and allowing them to communicate via a network gives rise to real-time cooperation in a multi-robotic team. This research presents a myriad of algorithms tested on a distributed system platform that allows for cooperating multi- agents in a dynamic environment. The test bed is an extension of a popular robot simulation system in the public domain developed at Carnegie Mellon University, known as TeamBots. A low-level real-time network game protocol using TCP/IP and UDP were incorporated to allow for a conglomeration of multi-agent to communicate and work cohesively as a team. Intelligent agents were defined to take on roles such as game coach agent, vision agent, and soccer player agents. Further, team cooperation is demonstrated by integrating a real-time fuzzy logic-based ball-passing algorithm and a fuzzy logic algorithm for path planning. Keywords Artificial Intelligence, Ball Passing, the coaching system, Collaborative, Distributed Multi-Agent, Fuzzy Logic, Role Assignmen

Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams

Mobile Robot Path Planning using Q-Learning with Guided Distance and Moving Target Concept

Classical Q-learning algorithm is a reinforcement of learning algorithm that has been applied in path planning of mobile robots. However, classical Q-learning suffers from slow convergence rate and high computational time. This is due to the random decision making for direction during the early stage of path planning. Such weakness curtails the ability of mobile robot to make instantaneous decision in real world application. In this study, the distance aspect and moving target concept were added to Q-learning in order to enhance the direction decision making ability and bypassing dead end. With the addition of these features, Q-learning is able to converge faster and generate shorter path. Consequently, the proposed improved Q-learning is able to achieve average improvement of 29.34-94.85%, 18.29-29.69% and 75.76-99.50% in time used, shortest distance and total distance used, respectively

Individual and coordinated decision for the CAMBADA team

Mestrado em Engenharia de Computadores e TelemáticaA coordenação em sistemas multi-robô é um aspecto crucial no futebol robótico. A maneira como cada equipa coordena cada um dos seus robôs em acções cooperativas define a base da sua estratégia. Este trabalho tem como foco o desenvolvimento da coordenação e estratégia da equipa CAMBADA. CAMBADA é a equipa de futebol robótico da modalidade RoboCup Middle Size League da Universidade de Aveiro. Foi desenvolvida pelo grupo ATRI, pertencente µa unidade de investigação IEETA. O presente trabalho baseia-se em trabalho desenvolvido anteriormente, tentando melhorar o desempenho da equipa. Cada robô da equipa CAMBADA é um agente independente e autónomo capaz de coordenar as suas acções com os colegas de equipa através da comunicação e da partilha de informação. O comportamento de cada robô deverá ser integrado na estratégia global da equipa, resultando assim em acções cooperativas de todos os robôs. Isto é conseguido através do uso de papeis(roles) e comportamentos(behaviours) que definem a atitude de cada robô e as acções que daí resultam. Novos papeis foram desenvolvidos para complementar a estratégia de equipa, e alguns dos papeis existentes foram melhorados. Também foram efectuadas melhorias em alguns dos comportamentos existentes. É efectu- ada a descrição de cada um destes papeis e comportamentos, assim como as alterações efectuadas. O trabalho desenvolvido foi testado nas competições do Robótica 2008 (o desenvolvimento não estava ainda concluído) e por fim nas competições do RoboCup'2008. A participação da equipa no RoboCup'2008 é analisada e discutida. A equipa consagrou-se campeã mundial, vencendo a competição da Middle Size League do RoboCup'2008 em Suzhou, China. ABSTRACT: Multi-robot coordination is one crucial aspect in robotic soccer. The way each team coordinates its individual robots into cooperative global actions define the foundation of its strategy. CAMBADA is the RoboCup Middle Size League robotic soccer team of the University of Aveiro. It was created by the ATRI group, part of the IEETA research unit. This work is focused on coordination and strategy development for the CAMBADA team. It is built upon previous work and tries to improve the team performance further. In CAMBADA each robot is an independent agent, it coordinates its actions with its teammates through communication and information exchange. The resulting behaviour of the individual robot should be integrated into the global team strategy, thus resulting in cooperative actions by all the robots. This is done by the use of roles and behaviours that define each robot attitude in the field and resulting individual actions. In this work, new roles were created to add to the team strategy and some of the previous existing roles were improved. Some of the existing behaviours were also improved to better fit the desired goals. Each role and behaviour is described as well as the changes made. The resulting work was put to test in the portuguese Robotica 2008 competition (while still in progress) and finally in the RoboCup'2008 world competitions. The performance of the team in the latter is analysed and discussed. The team achieved the 1st place in the RoboCup'2008 MSL world competitions

A Survey and Analysis of Multi-Robot Coordination

International audienceIn the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper

Coordinated multi-robot formation control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201