McGill Reddogs Computational Soccer Architecture McGill-RedDogs

Abstract. The approach of the McGill Red Dogs Sony Legged Robot system for soccer competition is described. A robotic system capable of playing soccer has many requirements that need to be met. Any soccer strategy is only as good as it can be executed on the underlying mobile platform. Our approach uses customized ambulation and vision to achieve dynamic localization and global map maintenance. This global map will provide information to modify a behavior state-transition engine as the match evolves. Behavior modes are switched on-the-fly to best suit the conditions that are detected, and to modularize design.

Computational Soccer Architecture

Abstract The approach of the McGill Red Dogs Sony Legged Robot system for soccer competition is described. A robotic system capable of playing soccer has many requirements that need to be met. Any soccer strategy is only as good as it can be executed on the underlying mobile platform. Our approach uses customized ambulation and vision to achieve dynamic localization and global map maintenance. This global map will provide information to modify a behavior state-transition engine as the match evolves. Behavior modes are switched on-the-fly to best suit the conditions that are detected, and to modularize design. 1 Introduction Any soccer strategy is only as good as it can be executed on the underlying mobile platform. The approach adopted was largely aimed at having a strong flexible mobile robotic core abilities for use to achieve relatively simple short term goals. A process timing kernel has been developed to allow for the parallel execution of these systems together with the behavior mechanisms in a manner that allows for custom dedication of computing resources. Robust locomotion and vision systems run concurrently and combine to give robust estimates for higher level behavior despite noisy measurements. Locomotion is scalable and capable of stable turning over a wide range of radii. Vision is based on probabilistic scene reconstruction using various voting heuristics