Simulation Tools for the Study of the Interaction between Communication and Action in Cognitive Robots

In this thesis I report the development of FARSA (Framework for Autonomous Robotics Simulation and Analysis), a simulation tool for the study of the interaction between language and action in cognitive robots and more in general for experiments in embodied cognitive science. Before presenting the tools, I will describe a series of experiments that involve simulated humanoid robots that acquire their behavioural and language skills autonomously through a trial-and-error adaptive process in which random variations of the free parameters of the robots’ controller are retained or discarded on the basis of their effect on the overall behaviour exhibited by the robot in interaction with the environment. More specifically the first series of experiments shows how the availability of linguistic stimuli provided by a caretaker, that indicate the elementary actions that need to be carried out in order to accomplish a certain complex action, facilitates the acquisition of the required behavioural capacity. The second series of experiments shows how a robot trained to comprehend a set of command phrases by executing the corresponding appropriate behaviour can generalize its knowledge by comprehending new, never experienced sentences, and by producing new appropriate actions. Together with their scientific relevance, these experiments provide a series of requirements that have been taken into account during the development of FARSA. The objective of this project is that to reduce the complexity barrier that currently discourages part of the researchers interested in the study of behaviour and cognition from initiating experimental activity in this area. FARSA is the only available tools that provide an integrated framework for carrying on experiments of this type, i.e. it is the only tool that provides ready to use integrated components that enable to define the characteristics of the robots and of the environment, the characteristics of the robots’ controller, and the characteristics of the adaptive process. Overall this enables users to quickly setup experiments, including complex experiments, and to quickly start collecting results

Categorisation through evidence accumulation in an active vision system

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A user interface for physical engine robot simulators

This report presents the architecture and some tests of a software that can be used for simulating the iCub robot\u27s arm and for building and simulating other robots. The software is based on OPAL to inteface either ODE or NEWTON physical engines, on YARP to allow parallel computation on multiple machines, and on REFLEX for monitoring simulation variables

Two Examples of Active Categorisation Processes Distributed Over Time

Active perception refers to a theoretical approach grounded on the idea that perception is an active process in which the actions performed by the agent play a constitutive role. In this paper we present two different scenarios in which we test active perception principles using an evolutionary robotics approach. In the first experiment, a robotic arm equipped with coarse-grained tactile sensors is required to perceptually categorize spherical and ellipsoid objects. In the second experiment, an active vision system has to distinguish between five different kinds of images of different sizes. In both situations the best individuals develop a close to optimal ability to discriminate different objects/images as well as an excellent ability to generalize their skills in new circumstances. Analyses of evolved behaviours show that agents are able to solve their tasks by actively selecting relevant information and by integrating these information over time

Comparison of genetic algorithms used to evolve specialisation in groups of robots

This paper investigates the role of genetic algorithms in determining which kind of specialisation emerges in decentralised simulated teams of robots controlled by evolved neural networks. As shown in previous works, different tasks may be better solved by robots specialized in a particular manner. However it was not clarified how much the genetic algorithm used might drive the evolution of one kind of specialisation or another: this is the goal of this paper. The study is conducted by evolving teams of robots that have to solve two different tasks that are better accomplished by using different types of specialisation (innate versus situated). Results suggest that the type of genetic algorithm employed plays a major role in determining how robots specialize and in most of the cases the algorithms used tend to always yield the same specialization. Only one of the algorithms tested led to the emergence of the most suitable kind of specialisation for each one of the two tasks

Trajectory learning through motor babbling: reaching with obstacle avoidance

According to one of the most influential principles of motor development theory, the circular-reaction hypothesis, infants perform exploratory random movements (motor babbling) to acquire efferent-reafferent associations later used to perform goal directed behavior. The models proposed so far to specify this principle learn to accomplish reaching tasks by using exploratory movements to associate final arm?s postures with stimuli. A limit of these models is that they cannot control the path followed by the hand to arrive to the target and so cannot cope with obstacles. This work proposes a model that starts to overcome this limitation, in particular it proposes a new neural-network architecture that uses motor babbling not to learn stimuli-final postures associations but to learn stimuli-trajectories associations through an Hebb rule. The system controls movement trajectories by regulating the parameters of two Time Based Generators that on their turn generate the sequence of desired positions of the arms? ?hand?. These types of associations render the system more flexible and capable of coping with obstacles. Preliminary tests run with a 2D kinematic arm demonstrate the viability of the proposed approach