Limited resources management in a RoboCup team vision system

Abstract

The vision system provides to a humanoid robot the most complete information about the environment, having thus visual information extraction a great influence in the decision process of interaction with the environment. It represents one of the most resources consumer in the system, so it has to be efficiently designed without compromising the reliability of the provided information. Software implementation of an accurate vision system is one of the more distinctive elements in RoboCup competitions, especially in the RoboCup Standard Platform League (Robocup SPL), where normative is becoming more and more restrictive and no hardware modifications can be made. In embedded control systems, management of the available resources is crucial to achieve a good performance and get the most from them. Focusing on the Robocup SPL, Nao robot has the CPU as the main shared and limited resource and, to a lesser degree, wireless network and memory should also be considered. In this work, the design of the vision module and the ability of the Hidalgos Team architecture to cope with limited resources are presented. The goal is to maximise CPU utilisation by boosting the capacities of the vision system, while maintaining control properties such as reactivity and stability. A first strategy emphasises on reducing resources consumed by the vision system through adaptability to control requirements. A second strategy focuses on adapting the execution rates of the modules, and especially of the vision system, to the available resources.