Robotic Homunculus: Learning of Artificial Skin Representation in a Humanoid Robot Motivated by Primary Somatosensory Cortex

Human skin relies on cutaneous receptors that output digital signals for tactile sensing in which the intensity of stimulation is converted to a series of voltage pulses. We present a power-efficient skin-inspired mechanoreceptor with a flexible organic transistor circuit that transduces pressure into digital frequency signals directly. The output frequency ranges between 0 and 200 hertz, with a sublinear response to increasing force stimuli that mimics slow-adapting skin mechanoreceptors. The output of the sensors was further used to stimulate optogenetically engineered mouse somatosensory neurons of mouse cortex in vitro, achieving stimulated pulses in accordance with pressure levels. This work represents a step toward the design and use of large-area organic electronic skins with neural-integrated touch feedback for replacement limbs.

We describe a humanoid robot platform--the iCub--which was designed to support collaborative research in cognitive development through autonomous exploration and social interaction. The motivation for this effort is the conviction that significantly greater impact can be leveraged by adopting an open systems policy for software and hardware development. This creates the need for a robust humanoid robot that offers rich perceptuo-motor capabilities with many degrees of freedom, a cognitive capacity for learning and development, a software architecture that encourages reuse & easy integration, and a support infrastructure that fosters collaboration and sharing of resources. The iCub satisfies all of these needs in the guise of an open-system platform which is freely available and which has attracted a growing community of users and developers. To date, twenty iCubs each comprising approximately 5000 mechanical and electrical parts have been delivered to several research labs in Europe and to one in the USA. Copyright © 2010 Elsevier Ltd. All rights reserved.

Traditionally, different classes of cutaneous mechanoreceptive afferents are ascribed different and largely non-overlapping functional roles (for example texture or motion) stemming from their different response properties. This functional segregation is thought to be reflected in cortex, where each neuron receives input from a single submodality. We summarize work that challenges this notion. First, while it is possible to design artificial stimuli that preferentially excite a single afferent class, most natural stimuli excite all afferents and most tactile percepts are shaped by multiple submodalities. Second, closer inspection of cortical responses reveals that most neurons receive convergent input from multiple afferent classes. We argue that cortical neurons should be grouped based on their function rather than on their submodality composition.