Methodology

We use the AIBO robots and the Open-R programming environment along with Tekkotsu framework in this project. We currently have two AIBO robots in our department. We have setup a Robocup soccer field in the AI Lab according to the formal specification described in the Robocup specification documents. The field includes two goals, four markers on sides of the field, a pink ball and white lines on the field.
AIBO robots are actually commercially available entertainment robots produced by Sony. Yet, there is an annual competition, Robocup Soccer, being done using the Aibo Robots. In addition, there is a fair amount of research being done on this domain using the robots. The research groups working on this area include Dutch AIBO Team, Carnegie Mellon Robocup Team, University of Pennsylvania AIBO Team and many others. Some of these research groups actually involve sub-groups from more than one universities.
Open-R SDK is the programming interface provided by SONY to be used in developing applications with the AIBO Robots. Open-R SDK is a development environment based on gcc (c++) where one can make software to run on AIBO (ERS-7, ERS-210, ERS-220, ERS-210A, and ERS-220A). It provides basic low-level functions to program the robot and access its hardware, memory and other units.
Tekkotsu framework is an open source development framework for the Sony AIBO developed by Carnegie Mellon University Tekkotsu Team. The aim of Tekkotsu framework is to build a structure on top of OPEN-R SDK environment using which people can develop more complex applications in a more easy and flexible way. That is it handles routine taks for the user, so that he or she can focus on higher level programming.
Since there are many issues to consider while developing an application using AIBO robots, we tried to make use of available projects and see how they work in order to get more things done in this project. For motion component, we are borrowing techniques from other well-established robocup teams such as UPenn and CMU which are already partly implemented in the Tekkotsu environment. Our localization is based on a Monte Carlo Localization routine [13] implementing a particle filter. To achieve the low level vision, we have very distinct markers in the field that we are able to identify through simple vision techniques, which aids us in localization.