Abstract
In this paper we propose a general active audition framework for auditory-driven Human-Robot Interaction (HRI). The proposed framework simultaneously processes speech and music on-the-fly, integrates perceptual models for robot audition, and supports verbal and non-verbal interactive communication by means of (pro)active behaviors. To ensure a reliable interaction, on top of the framework a behavior decision mechanism based on active audition policies the robot's actions according to the reliability of the acoustic signals for auditory processing. To validate the framework's application to general auditory-driven HRI, we propose the implementation of an interactive robot dancing system. This system integrates three preprocessing robot audition modules: sound source localization, sound source separation, and ego noise suppression; two modules for auditory perception: live audio beat tracking and automatic speech recognition; and multi-modal behaviors for verbal and non-verbal interaction: music-driven dancing and speech-driven dialoguing. To fully assess the system, we set up experimental and interactive real-world scenarios with highly dynamic acoustic conditions, and defined a set of evaluation criteria. The experimental tests revealed accurate and robust beat tracking and speech recognition, and convincing dance beat-synchrony. The interactive sessions confirmed the fundamental role of the behavior decision mechanism for actively maintaining a robust and natural human-robot interaction. © 2012 IEEE.

Abstract
The emergence of multi-agent systems in the past years has led to a necessity of developing new methodologies to assist in the requirements and architectural analysis, and in the design phases of such a system, and as a consequence, several Agent Oriented Software Engineering (AOSE) methodologies have been proposed. In this paper, we analyze the GAIA methodology and some proposed extensions, and use this methodology to design an abstract generic system model for an open multi-robot application. We then derive two distinct specific models for two different applications - the first with the intention of using intelligent wheelchairs in a hospital environment, and the second targeting the use of teams of autonomous aircrafts. The successful adoption of the generic model in the design stages of the two distinct systems not only validates the proposed model and shows that it can be used in open multi-agent systems, but also shows it is also flexible enough to be used in systems as diverse as these. By adapting the GAIA methodology for the design of open systems, this work enables designers to model open systems in a faster and simpler form, decreasing the time needed to complete several tasks, while maintaining a high-level overview of the system. ©2010 IEEE.

Abstract
Strategic planning and multi-agent coordination are major research topics in the domain of RoboCup. Research was, in the first years, directed towards development of low level skills and positional co-ordination. The competitive level has in between risen to new standards, which makes the development of high-level co-operation necessary. The importance of the concept of Setplay, i.e., small multi-robot plans to deal with particular situations, to structure a robotic soccer team behaviour, has been acknowledged by many researchers, but no general framework for the development and execution of generic Setplays has been introduced in the context of RoboCup. This paper presents such a framework for high-level Setplay definition and execution in the 2D simulation league, though applicable to any RoboCup co-operative league and similar domains. The framework is built upon a standard, flexible and league-independent language, which defines Setplays that are interpreted and executed at run-time, using inter-robot communication. A major step in the development of the Setplay framework is its usage and testing in the scope of the FCPortugal team, which participates in the RoboCup 2D-simulation league, where it won several titles. After this successful implementation, described in this paper, the framework will be used in the mid-size league, and possibly in other new environments. Recent developments have made it possible to use Setplays in play-on situations, which had not been possible before. Also, a graphical tool for Setplay definition has been developed, and used in the context of this team. ©2010 IEEE.

Abstract
The most common cause of traffic accidents is arguably the driver error due to lack of attention. And it is very unlikely this is going to change soon thanks to increasingly cell-phone usage, in-car entertainment systems, and naturally the more frequent traffic jams in highly populated areas. Autonomous vehicles, such as driverless cars, are a promising approach to decrease traffic accidents, as well as congestions. To test this approach, simulations are a safer, more efficient, and cheaper way than live testing. This paper presents an approach to implement a simulator to test such vehicles. It includes a study of the state of the art in driverless car simulation and discusses on the specific objectives that this particular simulator aims to achieve in order to aid testing the interactions of multiple driverless cars in urban networks.

Abstract
In this paper we propose the integration of an online audio beat tracking system into the general framework of robot audition, to enable its application in musically-interactive robotic scenarios. To this purpose, we introduced a state-recovery mechanism into our beat tracking algorithm, for handling continuous musical stimuli, and applied different multi-channel preprocessing algorithms (e. g., beamforming, ego noise suppression) to enhance noisy auditory signals lively captured in a real environment. We assessed and compared the robustness of our audio beat tracker through a set of experimental setups, under different live acoustic conditions of incremental complexity. These included the presence of continuous musical stimuli, built of a set of concatenated musical pieces; the presence of noises of different natures (e. g., robot motion, speech); and the simultaneous processing of different audio sources on-the-fly, for music and speech. We successfully tackled all these challenging acoustic conditions and improved the beat tracking accuracy and reaction time to music transitions while simultaneously achieving robust automatic speech recognition.

Abstract
In a soccer match, a cooperative behavior emerges from the combined execution of simple actions by players. A cooperative behavior can be planned if players are previously committed to its execution prior to its start or unplanned otherwise. The ability to reproduce some of these behaviors can be useful to help a team achieve better performances. This work presents an approach to identify and extract cooperative behaviors that start from set-pieces and lead to a goal while ball possession is kept. The representation of these behaviors is abstracted using a set-play definition language to promote their reusability. A set of game log files generated with the FC Portugal team and collected from the RoboCup 2010 2D simulated soccer competition were analyzed. The results achieved showed that 25% of the total goals scored originated from set-pieces which attests to the importance of performing this analysis. Several guidelines for the definition of future set-plays were also inferred. In the future, these behaviors shall be tested to infer which are capable of neutralizing an opponent's team strategy and maximize the creation of goal opportunities.