Mirando al camino

As outlined above, an important aspect of the developmental cognitive robotics paradigm is the inclusion of an artificial body in the cognitive modelling process.

Consequently, designing a neuro-robotics experiment requires settling on the choice of a particular robot that will be appropriate for the research. The robotic plat-form used throughout the experiments described herein is the iCub humanoid robot (Metta, Sandini, Vernon, Natale & Nori, 2008; Metta et al., 2010, see figure 3).

The iCub platform, including the complete robot itself, as well as the accom-panying software, has been developed from scratch (Metta et al., 2010) within the European Commission-funded, sixth framework programme project RobotCub, headed by the Italian Institute of Technology, and completed in 2010 (RobotCub pro-ject website, 2013). At the time of writing, various versions of iCub are being used

in more than 20 research laboratories worldwide (iCub website, 2013), and ongo-ing projects aim at further developongo-ing the platform by providongo-ing it with additional capabilities, like whole-body motion interaction with multiple contacts (CoDyCo project website, 2013).

One of the primary motivations that guided the design of the iCub was the belief that ‘the physical instantiation of [. . .] [the models of the development of human cognition] in a behaving humanoid robot’ is one of the crucial ingredients necessary to allow the construction of cognitive systems to progress (Metta et al., 2010, p. 1126). The RobotCub project aimed therefore at providing a platform that would fulfil the present and future requirements of the researchers working on the development of cognition (Vernon, von Hofsten & Fadiga, 2010). In line with the view that object grasping is central to human cognition (Arbib, 2002b), strong emphasis has been put on the capabilities of the robot connected with manipulation.

On the mechatronics side, the iCub robot, shown in figure 3a, is approximately 1 meter tall and weights around 22 kilogrammes, what is intended to resemble the body dimensions of a 3- to 4-years-old child (Metta et al., 2010). Its upper body incorporates the total of 38 actuated degrees of freedom (dof). 6 of these are alloc-ated to the head, 3 implementing the full range of neck motions, and 3 supporting the movements of the eyes, including vergence. Each of the arms of the robot has 7 dof: 3 in the shoulder joint, and 2 in both elbow and wrist. The robot’s hands have 9 dof, allowing for considerable dexterity and reflecting the design emphasis on ma-nipulation (see figure 3b). The first three fingers can be controlled independently, while the ‘ring’ and ‘pinkie’ fingers are linked together under 1 dof, providing addi-tional support and stability for grasping. The manipulation capabilities are further extended by 3 dof in the robot waist that increase the reachable working space.

The original version of the iCub was designed to support crawling and sitting rather than walking, and therefore each of the legs has 6 dof. This brings the grand total of the actuated dof of the robot to 53. The legs of the robot were not used in the present study.

(a) (b)

(c)

Figure 3: iCub, the humanoid robot used in the present study. (a) the robot at the disposal of Plymouth University that has been used throughout the experiments described herein; (b) close-up of the iCub’s 16-dof arm; (c) the virtual counterpart of the robot as seen in the simulation software.

For the ‘static’ robotic experiments that do not involve crawling or sitting, the robot is used attached to a stand by its hip, as depicted in figure 3a. As iCub was not meant to be fully autonomous in terms of power supply and computational power (Metta et al., 2010), the connection with the external facilities is achieved through the ‘umbilical cord’ attached to the back of the robot. As mentioned earlier, a project that aims at upgrading the iCub’s lower body in order to enable using it in a free-standing set-up is under way (Eljaik et al., 2013; CoDyCo project website, 2013). For the time being, for experiments requiring mobility an optional mobile base for the robot, called iKart, is available.

The interaction of the iCub with its environment is realised through a range of sensors available on-board. Vision and audition are provided by the digital cameras located in the robot’s eyes and the microphones on both sides of its head, respect-ively. Proprioceptive sensing includes the inertial sensors located in the head (3 gyroscopes, 3 linear accelerometers and a compass), as well as the force/torque and position sensors in the body joints. Recently, the repertoire of the iCub’s sensing capabilities has been extended with an artificial modular skin that can be mounted on the robot’s fingers, palms, forearms and torso (Schmitz et al., 2011).

The entire design of the robot is open-source, which includes the robot’s soft-ware (Metta et al., 2010). The iCub-specific softsoft-ware architecture is developed on top of a more general middleware called yarp (Yet Another Robot Platform, Metta, Fitzpatrick & Natale, 2006). The latter provides operating system-independent fa-cilities for interfacing with the robot hardware as well as for implementing the robot control software in a modular way. The range of software available for the iCub robot is being constantly extended by an active community of users and researchers (iCub website, 2013). Among those, certain software tools were of particular importance for the present study. Firstly, the iCub simulator (Tikhanoff et al., 2008; Tikhanoff, Cangelosi & Metta, 2011) provides a virtual copy of the robot than can be used for developing and testing of the control software in a rapid and safe way without the need of the physical access to the robot (see figure 3c). The precision of the

simulation is usually sufficient to allow for an easy transition of the ready software to the real robot. Secondly, the yarp Cartesian interface (Pattacini, Nori, Natale, Metta & Sandini, 2010), together with its iCub-specific implementation, provides a solution for the robot’s inverse kinematics that enables the user to control the robot directly in its working space, using the Cartesian coordinates.

Overall, the motivations for using the iCub as the principal robot platform for the present study can be summarised as follows:

ˆ large number of the degrees of freedom in the upper body of the robot together with the humanoid design allow for faithful modelling of the counting gestures;

ˆ required capabilities (robot simulation, Cartesian control of the robot’s hands and gaze, position control and sensing) available out-of-the-box;

ˆ open-source robot software can be extended as needed;

ˆ easy and flexible interfacing of the available robot software with custom control software.

4.4 Artificial Neural Network Models Employed