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Modelling aspects of the human vision system, including the retina, is difficult due to insufficient knowledge about the internal components, organisation and complexity of the interactions within the system. Retinal ganglion cells are considered a core component of the human visual system as they convey the accumulated data as action potentials onto the(More)
This paper describes the application of a Convolutional Neural Network (CNN) in the context of a predator/prey scenario. The CNN is trained and run on data from a Dynamic and Active Pixel Sensor (DAVIS) mounted on a Summit XL robot (the predator), which follows another one (the prey). The CNN is driven by both conventional image frames and dynamic vision(More)
Even though artificial vision has been in development for over half a century it still fares poorly when compared to biological vision. The processing capabilities of biological visual systems are vastly superior in terms of power, speed, and performance. Inspired by this robust performance artificial vision systems have sought to take inspiration from(More)
Current approaches to networked robot systems (or ecology of robots and sensors) in ambient assisted living applications (AAL) rely on pre-programmed models of the environment and do not evolve to address novel states of the environment. Envisaged as part of a robotic ecology in an AAL environment to provide different services based on the events and user(More)
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