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The paper presents a neurorobotics cognitive model explaining the understanding and generalisation of nouns and verbs combinations when a vocal command consisting of a verb-noun sentence is provided to a humanoid robot. The dataset used for training was obtained from object manipulation tasks with a humanoid robot platform; it includes 9 motor actions and 9 objects placing placed in 6 different locations),...
This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co‐develop: individual learning about...
Neural networks have been used in many different robot motor-control experiments, however, so far the complexity of these neuro-controllers have remained at the similar level. The focus of this paper is to demonstrate that it is possible to scale-up these neuro-robotic controllers with GPUs leading to richer, more realistic and more complex motor control.
The modelling of the integration of various cognitive skills and modalities requires complex and computationally intensive algorithms running in parallel while controlling highperformance systems. The distribution of processing across many computers has certainly advanced our software ecosystem and opened up research to new possibilities. While this was an essential move, we are aspiring to augment...
This paper presents a novel open-source software application, Aquila, developed as a part of the ITALK and RobotDoC projects. The software provides many different tools and biologically-inspired models, useful for cognitive and developmental robotics research. Aquila addresses the need for high-performance robot control by adopting the latest parallel processing paradigm, based on the NVidia CUDA...
Autonomous navigation and robust obstacle avoidance are prerequisites for the successful operation of a planetary rover. Typical approaches to tackling this problem rely on complex and computationally expensive navigation strategies based upon the creation of 3D maps of the environment. In contrast, this research proposes a simple artificial neural network relying on infrared sensory input as the...
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