The iCub humanoid robot: An open-systems platform for research in cognitive development

By Giorgio Metta, Lorenzo Natale, F. Nori, Giulio Sandini, David Vernon, Luciano Fadiga, C. Von Hofsten, K. Rosander, Manuel Lopes, José Santos-Victor and 2 more. 2010

623 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Developmental and Educational Psychology, Social Psychology, Robotics & Control, Cognitive Science & Psychology

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Citations in the corpus

A Neurorobotic Experiment for Crossmodal Conflict Resolution in Complex Environments * (2018, methodology): “The goal of the neurorobotic experiment was to trigger human-like responses with an iCub [17] exposed to the same”
Challenging SMT solvers to verify neural networks (2012, neutral): “The original case studies are derived from MLPs used in real-world applications, namely the humanoids James [25] and iCub [28].”
Robotic Hand Pose Estimation Based on Stereo Vision and GPU-enabled Internal Graphical Simulation (2016, methodology): “We apply our framework to the iCub humanoid robot [29] (see Fig.”
Incremental robot learning of new objects with fixed update time (2016, background): “iCubWorld28 [30] is a dataset for visual object recognition in robotics, collected during a series of sessions where a human teacher showed different objects to the iCub humanoid robot [31].”
GRAIL: A Goal-Discovering Robotic Architecture for Intrinsically-Motivated Learning (2016, methodology): “In a recent work [72], we implemented a three-level hierarchical architecture to control the two redundant arms of the simulated iCub robot [50] tested in a reaching task within a 3-D environment.”
Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time (2016, background): “Indeed, this is essential for a robot which is expected to promptly react to external stimuli.”
Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network (2016, methodology): “Since we are interested in solving object recognition within a real robotic scenario, we performed our data acquisition on an actual robot, the iCub [12].”