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Proceedings ArticleDOI

An open-source simulator for cognitive robotics research: the prototype of the iCub humanoid robot simulator

TLDR
The prototype of a new computer simulator for the humanoid robot iCub, 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.
Abstract
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.

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Journal ArticleDOI

A Multimodal Connectionist Architecture for Unsupervised Grounding of Spatial Language

TL;DR: A bio-inspired unsupervised connectionist architecture is proposed and applied to grounding the spatial phrases and it is revealed that separate processing and representation of the spatial location and the object shape significantly improve the performance of the model.
Journal ArticleDOI

Generalisation, decision making, and embodiment effects in mental rotation

TL;DR: The work presented in this study overcomes limitations by proposing a novel neurorobotic model that has a macro-architecture constrained by knowledge held on brain, encompasses a rather general mental rotation mechanism, and incorporates a biologically plausible decision making mechanism.
Journal ArticleDOI

A review of abstract concept learning in embodied agents and robots.

TL;DR: This will include a discussion of the learning of abstract words such as ‘use’ and ‘make’ in humanoid robot experiments, and the acquisition of numerical concepts via gesture and finger counting strategies.
Journal ArticleDOI

Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots.

TL;DR: A Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels and show that the robot could successfully use the word meanings learned by using the proposed method.
Proceedings ArticleDOI

Learning task space control through goal directed exploration

TL;DR: An autonomous goal-directed strategy to learn how to control a redundant robot in the task space by using arm and waist motion, not relying on any prior knowledge or initial motor babbling is presented.
References
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Proceedings ArticleDOI

Design and use paradigms for Gazebo, an open-source multi-robot simulator

TL;DR: Gazebo is designed to fill this niche by creating a 3D dynamic multi-robot environment capable of recreating the complex worlds that would be encountered by the next generation of mobile robots.
Proceedings Article

The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems

TL;DR: Current usage of Player and Stage is reviewed, and some interesting research opportunities opened up by this infrastructure are identified.
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TL;DR: This book describes the basic concepts and methodologies of evolutionary robotics and the results achieved so far, and describes the clear presentation of a set of empirical experiments of increasing complexity.
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Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation:

TL;DR: Webots™ lets you define and modify a complete mobile robotics setup, even several different robots sharing the same environment, and enable you to transfer your control programs to several commercially available real mobile robots.
Journal ArticleDOI

YARP: Yet Another Robot Platform:

TL;DR: The goal of YARP is to minimize the effort devoted to infrastructure-level software development by facilitating code reuse, modularity and so maximize research-level development and collaboration by encapsulating lessons from the experience in building humanoid robots.
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