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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

Transfer learning with probabilistic mapping selection

TL;DR: Experimental results show that the use of multiple inter-task mappings, accompanied with a probabilistic selection mechanism, can significantly boost the performance of transfer learning relative to 1) learning without transfer and 2) using a single hand-picked mapping.
Proceedings ArticleDOI

The iCub learns numbers: An embodied cognition study

TL;DR: Results support the thesis that learning the number words in sequence, along with finger configurations helps the building of the initial representation of number in the robot.
Proceedings ArticleDOI

Self-supervised learning of tool affordances from 3D tool representation through parallel SOM mapping

TL;DR: This method enables the robot to accurately predict the effect of its actions using tools, and thus to select the best action for a given goal, even with tools not seen on the learning phase.
Journal ArticleDOI

Modelling mental rotation in cognitive robots

TL;DR: A system-level bio-constrained model that provides an embodied account of mental rotation processes relying on neural mechanisms involving motor affordance encoding, motor simulation and the anticipation of the sensory consequences of actions (both visual and proprioceptive).
Proceedings ArticleDOI

Towards the grounding of abstract words: A Neural Network model for cognitive robots

TL;DR: A model based on Artificial Neural Networks (ANNs) extends the symbol grounding mechanism to abstract words for cognitive robots to obtain a semantic representation of abstract concepts through the grounding in sensorimotor experiences for a humanoid robotic platform.
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.
MonographDOI

Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines

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.
Journal ArticleDOI

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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