27 research outputs found
Development of Cognitive Capabilities in Humanoid Robots
Merged with duplicate record 10026.1/645 on 03.04.2017 by CS (TIS)Building intelligent systems with human level of competence is the ultimate
grand challenge for science and technology in general, and especially for the
computational intelligence community. Recent theories in autonomous cognitive
systems have focused on the close integration (grounding) of communication with
perception, categorisation and action. Cognitive systems are essential for
integrated multi-platform systems that are capable of sensing and communicating.
This thesis presents a cognitive system for a humanoid robot that integrates
abilities such as object detection and recognition, which are merged with natural
language understanding and refined motor controls. The work includes three
studies; (1) the use of generic manipulation of objects using the NMFT algorithm,
by successfully testing the extension of the NMFT to control robot behaviour; (2) a
study of the development of a robotic simulator; (3) robotic simulation experiments
showing that a humanoid robot is able to acquire complex behavioural, cognitive,
and linguistic skills through individual and social learning. The robot is able to
learn to handle and manipulate objects autonomously, to cooperate with human
users, and to adapt its abilities to changes in internal and environmental conditions.
The model and the experimental results reported in this thesis, emphasise the
importance of embodied cognition, i.e. the humanoid robot's physical interaction
between its body and the environment
Markerless visual servoing on unknown objects for humanoid robot platforms
To precisely reach for an object with a humanoid robot, it is of central
importance to have good knowledge of both end-effector, object pose and shape.
In this work we propose a framework for markerless visual servoing on unknown
objects, which is divided in four main parts: I) a least-squares minimization
problem is formulated to find the volume of the object graspable by the robot's
hand using its stereo vision; II) a recursive Bayesian filtering technique,
based on Sequential Monte Carlo (SMC) filtering, estimates the 6D pose
(position and orientation) of the robot's end-effector without the use of
markers; III) a nonlinear constrained optimization problem is formulated to
compute the desired graspable pose about the object; IV) an image-based visual
servo control commands the robot's end-effector toward the desired pose. We
demonstrate effectiveness and robustness of our approach with extensive
experiments on the iCub humanoid robot platform, achieving real-time
computation, smooth trajectories and sub-pixel precisions
A Framework for Fast, Autonomous, and Reliable Tool Incorporation on iCub
One of the main advantages of building robots with size and motor capabilities close to those of humans, such as the iCub, lies in the fact that they can potentially take advantage of a world populated with tools and devices designed by and for humans. However, in order to be able to do proper use of the tools around them, robots need to be able to incorporate these tools, that is, to build a representation of the tool's geometry, reach and pose with respect to the robot. The present paper tackles this argument by presenting a repository which implements a series of interconnected methods that enable autonomous, fast and reliable tool incorporation on the iCub platform
An Open-Source Simulator for Cognitive Robotics Research: The Prototype of the iCub Humanoid Robot Simulator
This paper presents the prototype of a new computer simulator for the humanoid robot iCub. The iCub is a new open-source humanoid robot developed as a result of the “RobotCub” project, a collaborative European project aiming at developing a new open-source cognitive robotics platform. The iCub simulator has been developed as part of a joint effort with the European project “ITALK” on the integration and transfer of action and language knowledge in cognitive robots. This is available open-source to all researchers interested in cognitive robotics experiments with the iCub humanoid platform
Face Landmark-based Speaker-Independent Audio-Visual Speech Enhancement in Multi-Talker Environments
In this paper, we address the problem of enhancing the speech of a speaker of
interest in a cocktail party scenario when visual information of the speaker of
interest is available. Contrary to most previous studies, we do not learn
visual features on the typically small audio-visual datasets, but use an
already available face landmark detector (trained on a separate image dataset).
The landmarks are used by LSTM-based models to generate time-frequency masks
which are applied to the acoustic mixed-speech spectrogram. Results show that:
(i) landmark motion features are very effective features for this task, (ii)
similarly to previous work, reconstruction of the target speaker's spectrogram
mediated by masking is significantly more accurate than direct spectrogram
reconstruction, and (iii) the best masks depend on both motion landmark
features and the input mixed-speech spectrogram. To the best of our knowledge,
our proposed models are the first models trained and evaluated on the limited
size GRID and TCD-TIMIT datasets, that achieve speaker-independent speech
enhancement in a multi-talker setting
On the role of eye contact in gaze cueing
Most experimental protocols examining joint attention with the gaze cueing paradigm are "observational" and "offline", thereby not involving social interaction. We examined whether within a naturalistic online interaction, real-time eye contact influences the gaze cueing effect (GCE). We embedded gaze cueing in an interactive protocol with the iCub humanoid robot. This has the advantage of ecological validity combined with excellent experimental control. Critically, before averting the gaze, iCub either established eye contact or not, a manipulation enabled by an algorithm detecting position of the human eyes. For non-predictive gaze cueing procedure (Experiment 1), only the eye contact condition elicited GCE, while for counter-predictive procedure (Experiment 2), only the condition with no eye contact induced GCE. These results reveal an interactive effect of strategic (gaze validity) and social (eye contact) top-down components on the reflexive orienting of attention induced by gaze cues. More generally, we propose that naturalistic protocols with an embodied presence of an agent can cast a new light on mechanisms of social cognition
The design and validation of the R1 personal humanoid
In recent years the robotics field has witnessed an interesting new trend. Several companies started the production of service robots whose aim is to cooperate with humans. The robots developed so far are either rather expensive or unsuitable for manipulation tasks. This article presents the result of a project which wishes to demonstrate the feasibility of an affordable humanoid robot. R1 is able to navigate, and interact with the environment (grasping and carrying objects, operating switches, opening doors etc). The robot is also equipped with a speaker, microphones and it mounts a display in the head to support interaction using natural channels like speech or (simulated) eye movements. The final cost of the robot is expected to range around that of a family car, possibly, when produced in large quantities, even significantly lower. This goal was tackled along three synergistic directions: use of polymeric materials, light-weight design and implementation of novel actuation solutions. These lines, as well as the robot with its main features, are described hereafter