The authors have applied reinforcement learning methods to real robot tasks in several aspects. We selected a skill of soccer as a task for a vision-based mobile robot. In this paper, we explain two of our method; (1)learning a shooting behavior, and (2)learning a shooting with avoiding an opponent. These behaviors were obtained by a robot in simulation and tested in a real environment in RoboC...

The RoboCup simulation league is traditionally the league with the largest number of teams participating, both at the international competitions and worldwide. 2011 was no exception, with a total of 39 teams entering the 2D and 3D simulation competitions. This paper presents the champions of the competitions, WrightEagle from the University of Science and Technology of China in the 2D competiti...

For models that include spatial aspects, the description and recognition of spatio-temporal patterns is an important building block for the analysis of simulation trajectories. We propose an approach that makes use of user-definable qualitative spatial relations between moving entities to represent simulation trajectories as directed labeled graph. In this graph, spatio-temporal patterns can be...

Preparing for robot soccer competitions by empirically evaluating different possible game strategies has been rather limited in leagues using real robots. Such limitation comes from factors related to the difficulty of extensively experimenting with games with real robots, such as their inevitable wear and tear and their usual limited number. RoboCup real robot teams have therefore developed si...

Self-localisation, or the process of an autonomous agent determining its own position and orientation within some local environment, is a critical task in modern robotics. Although this task may be formally defined as a simple transformation between local and global coordinate systems, the process of accurately and efficiently determining this transformation is a complex task. This is particula...

This chapter discusses a top-down approach to modelling soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple robotic soccer leagues in the RoboCup. We investigate if and how soccer theory can be formalised such that specification and execution is possible. The advantage is clear: theory abstrac...

The RoboCup 2D Simulation League incorporates several challenging features, setting a benchmark for Artificial Intelligence (AI). In this paper we describe some of the ideas and tools around the development of our team, Gliders2012. In our description, we focus on the evaluation function as one of our central mechanisms for action selection. We also point to a new framework for watching log fil...

Robotic soccer, and RoboCup in particular, has been a research topic for almost a decade, with an upsurge during the last few years. RoboCup is usually viewed as being a means to research, education, and dissemination. We analyse RoboCup in each of these perspectives. Firstly, we show that RoboCup is a good research challenge. Second, we conclude that RoboCup is not always useful in education. ...

Robotic soccer is a challenging research area, which involves multiple agents that need to collaborate in an adversarial environment to achieve specific objectives. Here we describe the Sharif CESR small robot team, which was participated in Robocup 2001 small size league in Seattle, USA. This paper explains the overall architecture of our robotic soccer system. Figure 1 shows a picture of our ...

Our team, RoboCanes, was formed in January 2010 for the 3D Soccer Simulation League. One of the team members was the former team leader of Virtual Werder 3D (VW3D) from the University of Bremen. His move to the University of Miami induced taking the original source code from VW3D and porting it to the new requirements of the soccer server and robot model. In Fall 2011, RoboCanes decided to deve...