This paper describes the navigation system used for the UQ RoboRoos robot soccer team, runner up in the 1998 world RoboCup championships. The navigation system has been developed to cope with the dynamic environment of robot soccer. Two interacting levels of the system called the schema and cognitive levels respectively, have been used to solve two orthogonal problems in spatial navigation: lon...

Machine learning is a major branch of AI and a main research direction of multi-agent systems (MAS). With the emergence of various new complex systems, agent’s individual ability and the system’s intelligence level are urgently to be improved. Agent learning methods and agent architecture are studied in this paper and a new hybrid intelligent learning algorithm based on multi-agent is proposed....

Coordination among multiple robots has been extensively studied in the past years, since a number of practical tasks can be performed in a much more effective way by employing a fleet of coordinated robotic bases. In particular, distributed coordination among robotic soccer agents has been considered in the recent years within the framework offered by the RoboCup competitions, mostly in the sim...

RoboCup soccer is still host to frequent collisions between robots that lead to unsavory gameplan that is typically not allowed in human soccer. In the Standard Platform league where ultrasonic sensors are employed, these collisions are forbidden, but there is still leniency in the Humanoid League. Additionally, advanced behaviors, such as dribbling, require robust obstacle avoidance strategies...

Movement analysis is a fundamental ability for any kind of robot. It is especially important for determining and understanding the dynamics of the robot’s surrounding environment. In the case of robot soccer players, movement analysis is employed for determining the trajectory of relevant objects (ball, teammates, etc.). However, most of the existing movement analysis methods require the use of...

RoboCup soccer competitions are considered among the most challenging multi-robot adversarial environments, due to their high dynamism and the partial observability of the environment. In this paper we introduce a method based on a combination of Monte Carlo search and data aggregation (MCSDA) to adapt discrete-action soccer policies for a defender robot to the strategy of the opponent team. By...

Visual perception is the most important method for providing information about the competition environment for RoboCup Middle Size League (MSL) soccer robots. The paper reviews the advancement of visual perception in RoboCup MSL soccer robots from several points of view including the design and calibration of the vision system, the visual object recognitio...

In the field of robot soccer, mobile robots must exhibit high responsiveness to motion commands and possess precise pose control. This article presents a digital controller for pose stability convergence, developed to small-sized soccer robots. Special emphasis has been put on the design of a generic controller, which is suitable for any mobile robot with differential kinematics. The proposed a...

In this paper, we describe the GMD-Robots. These robots will be presented at the RoboCup 1999. RoboCup is the robot world cup soccer games and conferences. It offers the opportunity to examine a wide range of technologies in different research areas. RoboCup is a task for a team of multiple moving robots in a dynamic environment. In order for a robot team to actually perform a soccer game vario...

Over the past few years, soccer-playing humanoid robots advanced significantly. Elementary skills, such as bipedal walking, visual perception, and collision avoidance have matured enough to allow for dynamic and exciting games. In this paper, the three winning Humanoid League teams from the KidSize, TeenSize, and AdultSize class present their soccer systems. The KidSize winner team DARwIn used ...