Architecture for Living Neuronal Network Control of a mobile robot

The intelligent controlling mechanism of a typical mobile robot is usually 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. 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 (animat) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This paper details the components of the overall animat closed loop system architecture and reports on the evaluation of the results from preliminary real-life and simulated robot experiments.

Controlling a mobile robot with a biological brain

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Some recent research is ongoing in which biological neurons 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 hybrid systems can provide distinct insights into the operation of biological neural structures, and therefore, such research has immediate medical implications as well as enormous potential in robotics. The main aim of the research is to assess the computational and learning capacity of dissociated cultured neuronal networks. A hybrid system incorporating closed-loop control of a mobile robot by a dissociated culture of neurons has been created. The system is flexible and allows for closed-loop operation, either with hardware robot or its software simulation. The paper provides an overview of the problem area, gives an idea of the breadth of present ongoing research, establises a new system architecture and, as an example, reports on the results of conducted experiments with real-life robots.

Cascade dicopper architectures of a dibenzodioxatetraazamacrocycle

The dibenzodioxatetraazamacrocycle [26]pbz(2)N(4)O(2) was characterised by single crystal X-ray diffraction and the protonation constants of this compound and the stability constants of its copper(II) and lead(II) complexes were determined by potentiometry in water at 298.2 K in 0.10 mol dm(-3) in KNO3. Mono- and dinuclear complexes were found for both metal ions, the dinuclear complexes being the main species in the 5-7.5 pH range for copper(II) and 7.5-8.5 for lead(II). As expected the values of the stability constants for the copper(II) complexes are lower than those for related macrocycles containing only nitrogen atoms. The presence of mono- and dinuclear copper complexes was also confirmed by electrospray ionization mass spectrometry. These results suggest that the symmetric macrocyclic cavity of [26]pbZ(2)N(4)O(2) has enough space for the coordination of two metal ions. Additionally, NMR spectroscopy showed that the dinuclear complex of lead(II) has high symmetry. The equilibrium constants of the dinuclear copper(II) complexes and dicarboxylate anions (oxalate, malonate and succinate) were also determined in 0.10 mol dm-3 aqueous KNO3 solution. Only species containing one anion, Cu(2)H(h)LA((2+h)), were found, strongly suggesting that the anion bridges the two copper(II) ions. The binding constants of the cascade species formed by [Cu-2[26]pbZ(2)N(4)O(2)(H2O)(4+) with dicarboxylate anions decrease with the increase in length of the alkyl chain of the anion, a fact which was attributed to a higher conformational energy necessary for the rearrangement of the macrocycle to accommodate the larger anions bridging the two copper(II) centres. The variation of the magnetic susceptibility with temperature Of [Cu-2(H-2[26]pbz(2)N(4)O(2))(oxa)(3)]-4H(2)O and [Cu-2([26]pbz(2)N(4)O(2))(suc)Cl-2] were measured and the two complexes showed different behaviour. (c) 2007 Elsevier Ltd. All rights reserved.

Structural diversity in supramolecular architectures of Mn(II) through non-covalent interactions

Two mononuclear complexes of manganese(II), [Mn(OCN)(2)(phen)(2)] 1 and [Mn(NCO)(2)(bpy)(2)] 2 [1,10-phenanthroline (phen); 2,2'-bipyridine (bpy)], have been synthesized and characterized by single crystal X-ray analysis, infra-red spectroscopy and magnetic studies. The coordination structure of complex 2 is already reported. The cyanate anions are pendent in both the complexes. In 1, cyanate anion links manganese(II) through O-atom, whereas in 2 it coordinates through N-atom. The mononuclear fragments of 1 are built up to a supramolecular lamellar 3D architecture by pi-pi interactions only. On the other hand, mononuclear fragments of 2 are assembled to a 2D supramolecular brick-wall architecture by C-H-... pi interactions.

Utilisation of dendritic architectures in molecular recognition and self-assembly processes

This mini-review outlines recent key developments in the use of dendritic architectures in self-assembly processes via utilisation of molecular recognition motifs.

Advanced scalable algorithms for advanced architectures

With the latest advances in the area of advanced computer architectures we are seeing already large scale machines at petascale level and we are discussing exascale computing. All these require efficient scalable algorithms in order to bridge the performance gap. In this paper examples of various approaches of designing scalable algorithms for such advanced architectures will be given and the corresponding properties of these algorithms will be outlined and discussed. Examples will outline such scalable algorithms applied to large scale problems in the area Computational Biology, Environmental Modelling etc. The key properties of such advanced and scalable algorithms will be outlined.

Suboptimal system recovery from communication loss in a multi-robot localization scenario using EKF algorithms

This paper describes a multi-robot localization scenario where, for a period of time, the robot team loses communication with one of the robots due to system error. In this novel approach, extended Kalman filter (EKF) algorithms utilize relative measurements to localize the robots in space. These measurements are used to reliably compensate "dead-com" periods were no information can be exchanged between the members of the robot group.

Modeling and simulating a mathematical tool for multi-robot pattern transformation

The work reported in this paper is motivated by the need to investigate general methods for pattern transformation. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some agents in the pattern are introduced. The need for a mathematical tool and simulations for visualizing the behavior of a transformation method is highlighted. A mathematical method based on the Moebius transformation is proposed. The transformation method involves discretization of events for planning paths of individual robots in a pattern. Simulations on a particle physics simulator are used to validate the feasibility of the proposed method.

Robot-human interaction - practical experiments with a cyborg

This paper presents results to indicate the potential applications of a direct connection between the human nervous system and a computer network. Actual experimental results obtained from a human subject study are given, with emphasis placed on the direct interaction between the human nervous system and possible extra-sensory input. An brief overview of the general state of neural implants is given, as well as a range of application areas considered. An overall view is also taken as to what may be possible with implant technology as a general purpose human-computer interface for the future.

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.

Analysis of the Fugl-Meyer outcome measures assessing the effectiveness of robot-mediated stroke therapy

Robot-mediated therapies offer a new approach to neurorehabilitation. This paper analyses the Fugl-Meyer data from the Gentle/S project and finds that the two intervention phases (sling suspension and robot mediated therapy) have approximately equal value to the further recovery of chronic stroke subjects (on average 27 months post stroke). Both sling suspension and robot mediated interventions show a recovery over baseline and further work is needed to establish the common factors in treatment, and to establish intervention protocols for each that will give individual subjects a maximum level of recovery.

Dynamic automata for mobile robot learning

Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.