Mark Neal

Ystumtec Ltd.

Due to the costs of related technologies tracking studies typically use low numbers of animals as representative samples for whole group or species analysis, often without clear knowledge as to how representative these numbers are. The use of unmanned aerial vehicles (UAVs) has the potential to considerably improve radio frequency (RF) based tracki...

A number of types of neural network have been shown to be useful for a wide range of tasks, and can be “trained” in a large number of ways. This paper considers how it might be possible to train and run neural networks to respond in different ways under different prevailing circumstances, achieving smooth transitions between multiple learned behavi...

This paper describes a custom designed electrically powered, fully autonomous 2.73 metre long boat for survey and mapping tasks in locations unsuitable for larger, manned craft. This work was originally inspired by the desire to survey marine terminating calving glaciers in Greenland. The hull has been designed with a bump along the bottom to mount...

This paper describes the development, testing and operational results from a small, autonomous sailing vessel that was designed to be easily launched and retrieved by one person while carrying a 7.5 kg payload and with enough speed under sail to overcome reasonable current. The hull is 1.2 metres long and fits in the boot of a typical car. This pap...

A simple method for balancing the motor driver load across a six-wheeled rover is presented. This method uses the concept of inflammation to model the load on each motor driver by its temperature, decreasing the load as the local temperature increases. The method is compared with both the base case, where all motors run at a fixed load; and a relat...

The robots that operate autonomously for extended periods in remote environments are often limited to gather only small amounts of power through photovoltaic solar panels. Such limited power budgets make power management critical to the success of the robot's mission. Artificial endocrine controllers, inspired by the mammalian endocrine system, hav...

Fourier Transform Ion Cyclotron Resonance mass spectra exhibit improved resolving power, mass accuracy and signal-to-noise ratio when presented in absorption mode; a process which requires calculation of a phase correction function. Mass spectrometric images can contain many thousands of pixels; hence methods of decreasing the time required to solv...

This paper describes the design, development, construction and demonstration of a hybrid (sail and electric motor) powered, small, robotic research vessel. The two-metre vessel is capable of speeds of up to five knots under sail and six knots using an electric motor without the need for human interaction. It is launchable by two people from the bea...

Aerial photographs and images are used by a variety of industries, including farming, landscaping, surveying, and agriculture, as well as academic researchers including archaeologists and geologists. Aerial imagery can provide a valuable resource for analyzing sites of interest and gaining information about the structure, layout, and composition of...

This paper extends the CARDINAL architecture by Kim et al. (2005) to CARDINAL-E. CARDINAL-E keeps the innate immune system behaviour at every computer on the network and relocates the adaptive immune system behaviour to higher performance computers. Two paradigmatic shifts are achieved by this modification. First is the shift from standalone to sup...

The design of a prototype remote-controlled glacier-surveying robot, capable of taking accurate above- and below-water measurements of calving glacier fronts, using swath bathymetry and laser scanning hardware is presented. Data captured using the remote control system during field trials on the Lille Gletscher in western Greenland are informally c...

This paper describes the application of the receptor density algorithm, an artificial immune system, as used to detect chemicals from data provided by various spectrometers. The system creates chemical signatures which are matched to a library of known chemicals, allowing the positive identification of hazardous substances. The performance of the s...

Estimation of attitude and orientation is a critically important technique for ground wheeled autonomous robots like driverless cars. By means of attitude estimation, robots can not only evaluate the risk of overturning the vehicle, but also correct many sensor errors caused by robot motion or vibration. Traditionally, odometry (wheel encoders) is...

The availability of new geomatics technologies and methods has transformed the investigation of sediment transport rates using the morphological approach. Terrestrial laser scanning (TLS), in particular, has transformative potential for mapping river change in braided rivers since much of the bed is sub-aerially exposed at low flows. TLS offers the...

An inertial measurement unit (IMU) is an electronic device to measure vehicle states like attitude, orientation, velocity, and position. Recently, many low-cost micro electro mechanical systems (MEMS) IMUs have emerged for only several hundred US dollars [1]. These MEMS-IMUs usually consist of three-axis accelerometers,gyros and magnetometers. In c...

This paper describes work on a biologically inspired approach to long term power management in sailing robots. Sailing robots offer the promise of a flexible and low cost ocean observation platform which can either hold station at fixed points or sail transects. Biologically inspired techniques have previously been applied to other power management...

APIC (Automatic Pointing and Image Capture) is an automatic algorithm capable of identifying potential imaging targets in a single WAC (Wide Angled Camera) image and then reimaging these targets using a HRC (High Resolution Camera). Its aim is to maximise science data return from a rover exploration platform whilst minimising ground-based human int...

APIC (Automatic Pointing and Image Capture) is an automatic algorithm capable of identifying potential imaging targets in a single WAC (Wide Angled Camera) image and then reimaging these targets using a HRC (High Resolution Camera). Its aim is to maximise science data return from a rover exploration platform whilst minimising ground-based human int...

MOOPs (Miniature Ocean Observation Platforms) are small, low cost, lightweight sailing robots intended to form a simple and flexible platform for developing robotic sailing concepts and for entering the Microtransat Challenge. They are only 72 cm long, weigh 4 kg and can be easily transported and deployed. A variety of different configurations have...

This paper outlines our experiences in simulating sailing robots. It focuses on efforts to simulate a sailing robot, both in pure software and a “Hardware in the Loop” (HIL) simulation and compares these results with sailing a similar course using an actual robot. The software simulator is built upon an open source sailing game called Tracksail. Th...

Calving and submarine melt account for the majority of loss from the Antarctic and over 50% of that from the Greenland Ice Sheet. These ice-ocean processes are highly efficient mass-loss mechanisms, providing a rapid link between terrestrial ice (storage) and the oceanic sink (sea level/freshwater flux) which renders the ocean-outlet-ice sheet syst...

There is an increasing desire to deploy autonomous robots into harsh environments where humans do not wish to go or cannot go. These robots have only infrequent contact with human operators and therefore, must be highly autonomous, both in terms of control and energy. Sailing robots represent a good example of such robots as the primary locomotive...

The appearance-based approach towards robot navigation is based on a pixel-wise comparison of images. Recent research has shown that the Euclidean distance in image space provides a robust method for robot homing, navigation along routes and topological mapping. The objective of this paper is to investigate how image data can be reduced in order to...

This paper presents a simple mechanism for an autonomous sailing robot to detect when it is within close proximity to fixed obstacles and a reactive mechanism to avoid those obstacles. This is achieved by using a raster based map of the local area and raycasting from the boat's current position in order to determine the distance and heading to the...

This paper presents the novel use of the Neural-endocrine architecture for swarm robotic systems. We make use of a number of behaviours to give rise to emergent swarm behaviour to allow a swarm of robots to collaborate in the task of foraging. Results show that the architecture is amenable to such a task, with the swarm being able to successfully c...

The current generation of sailing robots require a small number of essential components in order to function successfully. These include some kind of sail and a device for de- tecting the direction of the wind, in order to ensure that the angle of attack of the sail is suitable for the course to be sailed. These two devices present some of the most...

We present an adaptive artificial neural-endocrine (AANE) system that is capable of learning ldquoon-linerdquo and exploits environmental data to allow for adaptive behaviour to be demonstrated. Our AANE is capable of learning associations between sensor data and actions, and affords systems the ability to cope with sensor degradation and failure....

Sailing robots provide a useful platform for investigations into autonomous robotics. Typically, sail boats involve one or more sails and a rudder. Recently, a two fixed-sail boat with no rudder has been proposed. In this paper, a P-controller is proposed for the control of this sail boat. It is shown that the heading of the boat can be controlled...

In this position paper, we outline a vision for a new type of engineering: immuno-engineering, that can be used for the development of biologically grounded and theoretically understood Artificial Immune Systems (AIS). We argue that, like many bio-inspired paradigms, AIS have drifted somewhat away from the source of inspiration. We also argue that...

Over the last four years we have developed five sailing robots of various sizes with the intention of performing long term ocean monitoring. These have demonstrated that a sailing robot could potentially perform long term ocean monitoring. A number of sensor packages, sail designs and hull designs have been tested. Wing sails have been found to be...

Biologically inspired approaches have long been touted as a possible mechanism to improve the survival of robots operating autonomously in harsh environments. One method which has often been suggested is to mimic the endocrine system which is responsible for the modulation of a series of behaviours. The endocrine system contributes to the process o...

The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches...

The desire to operate highly autonomous robots in harsh conditions which may threaten their survival has demonstrated the need for artificial systems which can adapt to their environment. Traditionally many have attempted to control robots with artificial neural networks (ANNs). These provide reasonably successful instantaneous reactive behaviours...

The natural immune system is composed of a diverse array of cells and proteins which cooperate to attack infections in the body. These cells interact in space and over time in two principal ways: through direct physical contact, and via intermediate signaling molecules. The network of these interactions is extremely complex and difficult to analyze...

The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches...

A model for integration of low-level responses to damage, potential damage and component failure in robots is presented. This model draws on the notion of inflammation and introduces an exten- sible, sub-symbolic mechanism for modulating high-level behaviour us- ing the notion of artificial inflammation. Preliminary results obtained via simulation...

The introduction of the Water Framework Directive has highlighted the need for water quality monitoring in freshwater systems, estuaries and at sea. Systems which currently exist for these tasks include fixed monitoring stations, both moored and drifting databuoys, survey ships and satellites. Moored databuoys suffer from significant costs in their...

A design for a sailing robot capable of holding station in a variety of wind and sea conditions is described. Results from experiments with an autonomously controlled small-scale prototype on a lake are also presented. The likely effects and problems of scale-up are examined, as are the cost considerations. Potential applications for a larger versi...

The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches...

Many researchers are developing frameworks inspired by natural, especially biological, systems to solve complex real-world problems. This work extends previous work in the field of biologically inspired computing, proposing an artificial endocrine system for autonomous robot navigation. Having intrinsic self-organizing behaviour, the novel artifici...

We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of Artificial Immune System (AIS) network models, and we discuss mathematica...

We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of Artificial Immune System (AIS) network models, and we discuss mathematica...

The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches...

The treatment of image data for robotic applications such as navigation, path planning and localization has always been problematic when working in image space (using the appearance of the environment) rather than in Cartesian space (using the geometry of the environment). This is due to both computational overhead introduced by the large amount of...

Abstract. This paper describes an artificial immune system algorithm which implements a fairly close analogue of the memory mechanism proposed by Jerne(1) (usually known as the Immune Network Theory). The algorithm demonstrates the ability of these types of network to produce meta-stable structures representing populated regions of the anti gen spac...

Responses labelled as emotional in the higher animals are frequently portrayed as incidental to the generation of reasonable behavior. Clearly this view is incompatible with the reality of animal behavior as observed in nature, emotion plays a significant role in the generation of useful behaviour. Homeostasis is the product of the interaction of t...

This paper presents an artificial immune system (AIS) which produces artificial immune networks that are meaningful, of a bounded size and dynamic over a very large number of data presentations. This behaviour had proved elusive up to this time but has now permitted the application of the AIS to situations requiring continuous learning. It also rem...

Robotic systems range from teleoperated to fully autonomous (where no human intervention takes place). The word “telerobotic” describes robotic systems which, although guided by a human, have a degree of autonomous behavior. This paper examines the tradeoff between the increasing design and implementation effort necessary as the system moves throug...

This paper presents a resource limited artificial immune system (RLAIS) for data analysis. The work presented here builds upon previous work on artificial immune systems (AIS) for data analysis. A population control mechanism, inspired by the natural immune system, has been introduced to control population growth and allow termination of the learni...

We present a simplified view of those parts of the human immune system which can be used to provide the basis for a data analysis tool. The motivation for and reasoning behind such a model is given and the desire for a 'transparent' model and meaningful visualization and interpretation techniques is noted. A minimalist formulation of an artificial...

Sectors of the food processing industry have challenging requirements for automation: short batches, product innovation, variation in component shape, all with high production volume. Hard-programmed automation cannot provide the flexibility required. We report our initial work on an approach in which robot operations are derived from the sensed di...

An analog implementation of a neuron using standard VLSI components is described. The node is capable of both delta-rule and simple error-correcting learning. Decomposition into functional blocks allows the parts of the design to be easily separated and understood. The connectivity problem is eased by serially encoding inputs so that all nodes in a...

This paper presents a resource limited artificial immune system for data analysis. The work presented here builds upon previous work on artificial immune systems for data analysis. A population control mechanism, inspired by the natural immune system, has been introduced to control population growth and allow termination of the learning algo- rithm...

Wilson,M.S. and Neal,M.J., 'Telerobotic Sheepdogs: how useful is autonomous behaviour?', Proceedings of the 6th International Conference on Simulation of Adaptive Behaviour, ed. Meyer,J.A. and Berthoz,A. and Floreano,D. and Roitblat,H.L. and Wilson,S.W., pp 125-134, 2000, MIT Press

Knowledge discovery in databases (KDD) is still a relatively new and expanding field. To aid the KDD process, data mining methods are used to extract previously unknown patterns and trends in vast amounts of data. There exist a number of data mining techniques, taking methods from the machine learning, statistical analysis and pattern recognition c...

This chapter Enscribes a machine learning system based on metaphors taken from the human immune system. This learning system, known as an Artificial Immune System (AIS), has been Enveloped over the past 3 years. The current implementation,Jisys,embodies the results of this research. However, the Jisys implementation requires further Envelopment as...

The human immune system can provide many metaphors that can be utilised effectively in the field of machine learning. These metaphors have been successfully applied to the complex real world problem of mortgage fraud detection, using a learning system known as Jisys. The Jisys system identifies patterns in mortgage fraud data by constructing an imm...

Thispaperdescribes at ool for converting data from a vector represmtation into an object oriented representation. The clases used to build objects are introduced. Analysis of the data and methods of desxribmg the objects to be built are discussed. Techniques used within this tool to automate the conversion process more fully are also described and...

Timmis J Neal M J and Hunt J. Augmenting an artificial immune network using ordering, self-recognition and histo-compatibility operators. In Proceedings of IEEE international conference of systems, man and cybernetics, pages 3821-3826, San Diego, 1998. IEEE.

This paper describes and evaluates the results of two algorithms for robotic grasp formulation on previously unseen 2-D thick laminae. Each algorithm determines the grasp specification from a binary image of the object to be grasped; one is an approach based on Powers’ Perceptual Control Theory and the other is based on hierarchical occupancy array...

The aim of this work is to investigate behavioural control strategies inspired by `perceptual control theory' demonstrated by Powers (1973), and their potential application in an industrial robotic handling task. In the particular approach reported here, an Adept robot is stationed over a conveyor belt which delivers the frozen food product pieces...

The implementation of artificial neural networks (ANNs) to the analysis of multivariate data is reviewed, with particular reference to the analysis of pyrolysis mass spectra. The need for and benefits of multivariate data analysis are explained followed by a discussion of ANNs and their optimisation. Finally, an example of the use of ANNs for the q...

Curie-point pyrolysis mass spectra were obtained from 30 Propionibacterium acnes strains isolated from the foreheads of six healthy humans. Multivariate analyses and Kohonen artificial neural networks (KANNs), employing unsupervised learning, were used successfully to discriminate between the P. acnes isolates from different individual hosts. The c...

The combination of pyrolysis mass spectrometry (PyMS) and artificial neural networks (ANNs) can be used to quantify levels of penicillins in strains of Penicillium chrysogenum and ampicillin in spiked samples of Escherichia coli. Four P. chrysogenum strains (NRRL 1951, Wis Q176, P1, and P2) were grown in submerged culture to produce penicillins, an...

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Binary mixtures of model systems consisting of the antibiotic ampicillin with either Escherichia coli or Staphylococcus auresu were subjected to pyrolysis mass spectrometry (PyMS). To deconvolute the pyrolysis mass spectra, so as to obtain quantitative information on the concentration of ampicilin in the mixtures, partial least squares regression (...

Binary mixtures of the protein lysozyme with glycogen, of DNA or RNA in glycogen, and the tertiary mixture of cells of the bacteria Bacillus subtilis, Escherichia coli, and Staphylococcus aureus were subjected to pyrolysis mass spectrometry. To analyze the pyrolysis mass spectra so as to obtain quantitative information representative of the complex...

Curie-point pyrolysis mass spectra were obtained from reference Propionibacterium strains and canine isolates. Artificial neural networks (ANNs) were trained by supervised learning (with the back-propagation algorithm) to recognize these strains from their pyrolysis mass spectra; all the strains isolated from dogs were identified as human wild type...

ABSTRACT The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching,the level of behaviour for which the artificial intelligence and robotics communities,strive. We suggest that it is now time to move on to integrating a number of these a...

We present a framework which integrates artificial neural networks, artificial im-mune systems and a novel artificial endocrine system. The natural counterparts of these three components are usually assumed to be the principal actors in main-taining homeostasis within biological systems. This paper proposes a system which promises to capitalise on...