aquila.sourceforge.netAquila: Welcome to Aquila project! - WORK IN PROGRESS

Aquila 2.0 prealpha Cognitive Robotics Architecture Main Page Related Pages Modules Namespaces Classes Files All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Groups Pages Welcome to Aquila project! - WORK IN PROGRESS The modelling of the integration of various cognitive skills and modalities requires complex and computationally intensive algorithms running in parallel while controlling high-performance systems. The distribution of processing across many computers has certainly advanced our software ecosystem and opened up research to new possibilities. While this was an essential move, we would like to augment the possibilities in cognitive robotics research by providing an easy-to-use, hi-performance, modular and scalable software architecture. This paper presents Aquila 2.0, an open-source cross-platform software architecture that makes use of independent heterogeneous CPU-GPU modules that can run anywhere across the network in any number of instances and using any number of available GPU devices. These modules are loosely coupled with their graphical user interfaces dynamically generated by Aquila on demand. In the following sections we provide a full description of the software architecture together with the instructions on how to use it and develop new modules with integrated tools that automate the process thus saving a considerable amount of time. Introduction Cognitive robotics is highly multidisciplinary filed concerned with endowing robots with high-level cognitive capabilities to enable the achievement of complex goals in complex environments. The cognitive capabilities include perception processing, attention allocation, planning, anticipation and reasoning about their own mental states and about other agents. Creating cognitive robots is challenging task demanding collaboration between researchers from different backgrounds (e.g. computer scientists, roboticists, neuroscientists, philosophers, linguists, etc.) and industries that are able to produce and deliver specific hardware and related software. Such collaborations are flourishing in environments that encourage producing hardware and software that everyone can use, reuse or extend. One of the most outstanding projects that embarked on such mission is RobotCub, which involved consortium of several European universities extensively collaborating with industries worldwide. RobotCub project strictly followed an open-source philosophy, which led to the design of one of the most advanced humanoid robots in the world named iCub (Cognitive Universal Body) (www.icub.org). iCub is a small humanoid robot approximately 105cm high, weights around 20.3kg and its design was inspired by the embodied cognition hypothesis. In addition, Tikhanoff et al. have developed an open-source simulated model of the iCub, which enabled researchers and students worldwide to get involed and start contributing without access to a physical robot. The simulator has been also widely adopted as a functional tool within the cognitive robotics community, as it allows researchers to develop, test and evaluate their models and theories before using them on the actual robot. Worldwide collaboration of researchers and industries is not only essential to develop robust hardware, sound scientific methods but also vital for the development of software that can facilitate bootstrapping of cognitive skills through constant interaction with the environment while dealing with influx of stimuli from multiple different sensory modalities. The iCub robot is a true achievement when it comes to the number of joints that can be controlled (53 deg. of freedom) and the variety of different sensors that can accessed (vision, sound, skin, touch sensors, force-torque sensors, position sensors, gyroscopes). Dealing with so much data while running software designed to make sense of it has been a challenge for years. Fitzpartick et al. have developed YARP (Yet Another Robotic Platform), which addressed this issue, standardised the software development and encouraged platform-independence, modularity, scalability and reuse via location-independent processes that can independently communicate via hardware-non-specific protocols. Good documentation and tutorials provided by YARP and iCub software developers led to many new modules being contributed to the iCub software repository, which on its part helped the development of higher-level modules inheriting functionalities of the existing modules. A good YARP module is typically independent from graphical user interface ( GUI ), easy to compile, runs on any platform and can be communicated with via network ports. YARP manager can be used in case of the requirement to connect multiple different modules together and/or run them on different computers across network. It is also possible to connect the output of some of the modules to the input of YARP viewers that can then display the incoming images, which helps provides a user with good feedback. Some modules such as robotMotorGui or iCubGui provide nice graphical user interfaces while others do not need or have one. If they do have a GUI then they are typically tied to run on a machine with running x-server and cannot be run elsewhere, which is perfectly fine for certain type of modules such as the already mentioned robotMotorGui or iCubGui. However, in cognitive robotics, we often use complex biologically-inspired models where a good graphical user interfaces and visualisation tools are essential to be able to understand and easily manage system behaviour. The training of large-scale artificial neural networks, self-organising maps, running image-processing or any other task should be able to run on any computer and make the most of its resources without compromising or completely removing their GUIs. We have been working with students and cognitive robotics researchers for several years now and our experience is that not all are skilled programmers. In fact, some are just looking to use certain features of the iCub (e.g. record vision, sensorimotor movements, control objects in the simulator) and others would like to develop their own modules with a nice graphical user interfaces and the ability ro run heterogeneous CPU-GPU modules in any number of instances anywhere across the network while centralising their management and GUI parts on the machine they are using for visualisation. The technical challenges involved in this, however, discourage many from embarking on such development. We present Aquila Cognitive Robotics Architecture that addresses these issues and was developed by researchers for researchers, students and enthusiasts who do not necessarily want to spend days writing new modules. Aquila provides a clearly structured architecture that separates modules from their GUI counterparts easily manageable via simple, yet powerful graphical interface that comes with Aquila. Developing a new module together with a graphical interface takes little time thanks to one of Aquila's tools called Module Generator, which creates an empty module and GUI with user-specified names. Module Generator updates all the necessary project files and connects the module with its GUI counterpart. After a module is generated, a user can add the required functionalities to the already existing structure and then launch the module anywhere across the network, in any number of instances using any available processors, which includes both CPUs and GPUs. The next section talks about the main motivation behind Aquila development, which is followed by the description of its architecture. The Developers section provides useful guidelines and tips for those who would like to develop their own modules. The Installation section explains three necessary steps to get Aquila up and running, which is followed by the last part with our conclusions. Software architecture diagram highlighting the loose coupling between a module and ...