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.

How soccer players head the ball: a test of optic acceleration cancellation theory with virtual reality

We measured the movements of soccer players heading a football in a fully immersive virtual reality environment. In mid-flight the ball’s trajectory was altered from its normal quasi-parabolic path to a linear one, producing a jump in the rate of change of the angle of elevation of gaze (α) from player to ball. One reaction time later the players adjusted their speed so that the rate of change of α increased when it had been reduced and reduced it when it had been increased. Since the result of the player’s movement was to regain a value of the rate of change close to that before the disturbance, the data suggest that the players have an expectation of, and memory for, the pattern that the rate of change of α will follow during the flight. The results support the general claim that players intercepting balls use servo control strategies and are consistent with the particular claim of Optic Acceleration Cancellation theory that the servo strategy is to allow α to increase at a steadily decreasing rate.

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.

Test performance indicators from a single soccer specific fitness test differentiate between highly trained and recreationally active soccer players

Aim. The aim of this study was to investigate whether a single soccer specific fitness test (SSFT) could differentiate between highly trained and recreationally active soccer players in selected test performance indicators. Methods. Subjects: 13 Academy Scholars (AS) from a professional soccer club and 10 Recreational Players (RP) agreed to participate in this study. Test 1-(V)over dotO(2) max was estimated from a progressive shuttle run test to exhaustion. Test 2-The SSFT was controlled by an automated procedure and alternated between walking, sprinting, jogging and cruise running speeds. Three activity blocks (1A, 2A and 3A) were separated by 3 min rest periods in which blood lactate samples were drawn. The 3 blocks of activity (Part A) were followed by 10 min of exercise at speeds alternating between jogging and cruise running (Part B). Results. Estimated (V)over dotO(2) max did not significantly differ between groups, although a trend for a higher aerobic capacity was evident in AS (p<0.09). Exercising heart rates did not differ between AS and RP, however, recovery heart rates taken from the 3 min rest periods were significantly lower in AS compared with RP following blocks 1A (124.65 b(.)min(-1) +/-7.73 and 133.98 b(.)min(-1) +/-6.63), (p<0.05) and 3A (129.91 b.min(-1) +/-10.21 and 138.85 b.min(-1) +/-8.70), (p<0.01). Blood lactate concentrations were significantly elevated in AS in comparison to RP following blocks 2A (6.91 mmol(.)l(-1) +/-2.67 and 4.74 mmol(.)l(-1) +/-1.28) and 3A (7.18 mmol(.)l(-1) +/-2.97 and 4.88 mmol(.)l(-1) +/-1.50), (p<0.05). AS sustained significantly faster average sprint times in block 3A compared with RP (3.18 sec +/-0.12 and 3.31 sec +/-0.12), (p<0.05). Conclusion. The results of this study show that highly trained soccer players are able to sustain, and more quickly recover from, high intensity intermittent exercise.

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.

Closely coupled behaviour in networked robot systems

Multiple cooperating robot systems may be required to take up a closely coupled configuration in order to perform a task. An example is extended baseline stereo (EBS), requiring that two robots must establish and maintain for a certain period of time a constrained kinematic relationship to each other. In this paper we report on the development of a networked robotics framework for modular, distributed robot systems that supports the creation of such configurations. The framework incorporates a query mechanism to locate modules distributed across the two robot systems. The work presented in this paper introduces special mechanisms to model the kinematic constraint and its instantiation. The EBS configuration is used as a case study and experimental implementation to demonstrate the approach.