Architecture for neuronal cell control of a mobile robot

It is usually expected that the intelligent controlling mechanism of a robot is a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot - thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. In particular, the use of rodent primary dissociated cultured neuronal networks for the control of mobile `animals' (artificial animals, a contraction of animal and materials) is a novel approach to discovering the computational capabilities of networks of biological neurones. A dissociated culture of this nature requires appropriate embodiment in some form, to enable appropriate development in a controlled environment within which appropriate stimuli may be received via sensory data but ultimate influence over motor actions retained. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animal) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This 'closed loop' interaction with the environment through both sensing and effecting will enable investigation of its learning capacity This paper details the components of the overall animat closed loop system and reports on the evaluation of the results from the experiments being carried out with regard to robot behaviour.

VERA: virtual environment for research in archaeology

The VERA (Virtual Environment for Research in Archaeology) project is based on a research excavation of part of the large Roman town at Silchester, which aims to trace the site's development from its origins before the Roman conquest to its abandonment in the fifth century A.D. [1]. The VERA project aims to investigate how archaeologists use Information Technology (IT) in the context of a field excavation, and also for post-excavation analysis. VERA is a two-year project funded by the JISC VRE 2 programme that involves researchers from the University of Reading, University College London, and York Archaeological Trust. The overall aim of the project is to assess and introduce new tools and technologies that can aid the archaeological processes of gathering, recording and later analysis of data on the finds and artefacts discovered. The researchers involved in the project have a mix of skills, ranging from those related to archaeology, and computer science, though to ones involving usability and user assessment. This paper reports on the status of the research and development work undertaken in the project so far; this includes addressing various programming hurdles, on-site experiments and experiences, and the outcomes of usability and assessment studies.

Towards natural human computer interaction in BCI

BCI systems require correct classification of signals interpreted from the brain for useful operation. To this end this paper investigates a method proposed in [1] to correctly classify a series of images presented to a group of subjects in [2]. We show that it is possible to use the proposed methods to correctly recognise the original stimuli presented to a subject from analysis of their EEG. Additionally we use a verification set to show that the trained classification method can be applied to a different set of data. We go on to investigate the issue of invariance in EEG signals. That is, the brain representation of similar stimuli is recognisable across different subjects. Finally we consider the usefulness of the methods investigated towards an improved BCI system and discuss how it could potentially lead to great improvements in the ease of use for the end user by offering an alternative, more intuitive control based mode of operation.

Phase resetting as a mechanism of ERP generation: evidence from the power spectrum

A Neural Mass model is coupled with a novel method to generate realistic Phase reset ERPs. The power spectra of these synthetic ERPs are compared with the spectra of real ERPs and synthetic ERPs generated via the Additive model. Real ERP spectra show similarities with synthetic Phase reset ERPs and synthetic Additive ERPs.

Museum robots: multi-robot systems for public exhibition

Mobile robots provide a versatile platform for research, however they can also provide an interesting educational platform for public exhibition at museums. In general museums require exhibits that are both eye catching and exciting to the public whilst requiring a minimum of maintenance time from museum technicians. In many cases it is simply not possible to continuously change batteries and some method of supplying continous power is required. A powered flooring system is described that is capable of providing power continuously to a group of robots. Three different museum exhibit applications are described. All three robot exhibits are of a similar basic design although the exhibits are very different in appearance and behaviour. The durability and versatility of the robots also makes them extremely good candidates for long duration experiments such as those required by evolutionary robotics.