A mathematical model, implementation and study of a swarm system

The work reported in this paper is motivated towards the development of a mathematical model for swarm systems based on macroscopic primitives. A pattern formation and transformation model is proposed. The pattern transformation model comprises two general methods for pattern transformation, namely a macroscopic transformation method and a mathematical transformation method. The problem of transformation is formally expressed and four special cases of transformation are considered. Simulations to confirm the feasibility of the proposed models and transformation methods are presented. Comparison between the two transformation methods is also reported.

On differentiating ground clutter and insect echoes from Doppler weather radars using archived data

Normally wind measurements from Doppler radars rely on the presence of rain. During fine weather, insects become a potential radar target for wind measurement. However, it is difficult to separate ground clutter and insect echoes when spectral or polarimetric methods are not available. Archived reflectivity and velocity data from repeated scans provide alternative methods. The probability of detection (POD) method, which maps areas with a persistent signal as ground clutter, is ineffective when most scans also contain persistent insect echoes. We developed a clutter detection method which maps the standard deviation of velocity (SDV) over a large number of scans, and can differentiate insects and ground clutter close to the radar. Beyond the range of persistent insect echoes, the POD method more thoroughly removes ground clutter. A new, pseudo-probability clutter map was created by combining the POD and SDV maps. The new map optimised ground clutter detection without removing insect echoes.

Force distribution in manipulation by a robot hand with equality and inequality constraints

The problem of the appropriate distribution of forces among the fingers of a four-fingered robot hand is addressed. The finger-object interactions are modelled as point frictional contacts, hence the system is indeterminate and an optimal solution is required for controlling forces acting on an object. A fast and efficient method for computing the grasping and manipulation forces is presented, where computation has been based on using the true model of the nonlinear frictional cone of contact. Results are compared with previously employed methods of linearizing the cone constraints and minimizing the internal forces.

A survey of multi-fingered robot hands: issues and grasping achievements

Recently a substantial amount of research has been done in the field of dextrous manipulation and hand manoeuvres. The main concern has been how to control robot hands so that they can execute manipulation tasks with the same dexterity and intuition as human hands. This paper surveys multi-fingered robot hand research and development topics which include robot hand design, object force distribution and control, grip transform, grasp stability and its synthesis, grasp stiffness and compliance motion and robot arm-hand coordination. Three main topics are presented in this article. The first is an introduction to the subject. The second concentrates on examples of mechanical manipulators used in research and the methods employed to control them. The third presents work which has been done on the field of object manipulation.

Bi-directional human machine interface via direct neural connection

This paper presents an application study into the use of a bi-directional link with the human nervous system by means of an implant, positioned through neurosurgery. Various applications are described including the interaction of neural signals with an articulated hand, a group of cooperative autonomous robots and to control the movement of a mobile platform. The microelectrode array implant itself is described in detail. Consideration is given to a wider range of possible robot mechanisms, which could interact with the human nervous system through the same technique.

Experimental measurement and numerical simulation of horizontal-coupled slinky ground source heat exchangers

Results from both experimental measurements and 3D numerical simulations of Ground Source Heat Pump systems (GSHP) at a UK climate are presented. Experimental measurements of a horizontal-coupled slinky GSHP were undertaken in Talbot Cottage at Drayton St Leonard site, Oxfordshire, UK. The measured thermophysical properties of in situ soil were used in the CFD model. The thermal performance of slinky heat exchangers for the horizontal-coupled GSHP system for different coil diameters and slinky interval distances was investigated using a validated 3D model. Results from a two month period of monitoring the performance of the GSHP system showed that the COP decreased with the running time. The average COP of the horizontal-coupled GSHP was 2.5. The numerical prediction showed that there was no significant difference in the specific heat extraction of the slinky heat exchanger at different coil diameters. However, the larger the diameter of coil, the higher the heat extraction per meter length of soil. The specific heat extraction also increased, but the heat extraction per meter length of soil decreased with the increase of coil central interval distance.

Free atmospheric CO2 enrichment increased above ground biomass but did not affect symbiotic N2-fixation and soil carbon dynamics in a mixed deciduous stand in Wales

Through increases in net primary production (NPP), elevated CO2 is hypothesizes to increase the amount of plant litter entering the soil. The fate of this extra carbon on the forest floor or in mineral soil is currently not clear. Moreover, increased rates of NPP can be maintained only if forests can escape nitrogen limitation. In a Free atmospheric CO2 Enrichment (FACE) experiment near Bangor, Wales, 4 ambient CO2 and 4 FACE plots were planted with patches of Betula pendula, Alnus glutinosa and Fagus sylvatica on a former arable field. Four years after establishment, only a shallow L forest floor litter layer had formed due to intensive bioturbation. Total soil C and N contents increased irrespective of treatment and species as a result of afforestation. We could not detect an additional C sink in the soil, nor were soil C stabilization processes affected by FACE. We observed a decrease of leaf N content in Betula and Alnus under FACE, while the soil C/N ratio decreased regardless of CO2 treatment. The ratio of N taken up from the soil and by N2-fixation in Alnus was not affected by FACE. We infer that increased nitrogen use efficiency is the mechanism by which increased NPP is sustained under elevated CO2 at this site.

Effect of soil waterlogging on below-ground biomass allometric relations in Norway spruce

An increasing importance is assigned to the estimation and verification of carbon stocks in forests. Forestry practice has several long-established and reliable methods for the assessment of aboveground biomass; however we still miss accurate predictors of belowground biomass. A major windthrow event exposing the coarse root systems of Norway spruce trees allowed us to assess the effects of contrasting soil stone and water content on belowground allocation. Increasing stone content decreases root/shoot ratio, while soil waterlogging leads to an increase in this ratio. We constructed allometric relationships for belowground biomass prediction and were able to show that only soil waterlogging significantly impacts model parameters. We showed that diameter at breast height is a reliable predictor of belowground biomass and, once site-specific parameters have been developed, it is possible to accurately estimate belowground biomass in Norway spruce.

An enhancement of the ionospheric sporadic‐E layer in response to negative polarity cloud‐to‐ground lightning

Lightning data, collected using a Boltek Storm Tracker system installed at Chilton, UK, were used to investigate the mean response of the ionospheric sporadic-E layer to lightning strokes in a superposed epoch study. The lightning detector can discriminate between positive and negative lightning strokes and between cloud-to-ground ( CG) and inter-cloud ( IC) lightning. Superposed epoch studies carried out separately using these subsets of lightning strokes as trigger events have revealed that the dominant cause of the observed ionospheric enhancement in the Es layer is negative cloud-to-ground lightning.

Autonomous ship collision free trajectory navigation and control algorithms

A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.

Neural network control of a simple mobile robot

In recent years researchers in the Department of Cybernetics have been developing simple mobile robots capable of exploring their environment on the basis of the information obtained from a few simple sensors. These robots are used as the test bed for exploring various behaviours of single and multiple organisms: the work is inspired by considerations of natural systems. In this paper we concentrate on that part of the work which involves neural networks and related techniques. These neural networks are used both to process the sensor information and to develop the strategy used to control the robot. Here the robots, their sensors, and the neural networks used and all described. 1.

Visual surveillance using deformable models of vehicles

This paper presents recent developments to a vision-based traffic surveillance system which relies extensively on the use of geometrical and scene context. Firstly, a highly parametrised 3-D model is reported, able to adopt the shape of a wide variety of different classes of vehicle (e.g. cars, vans, buses etc.), and its subsequent specialisation to a generic car class which accounts for commonly encountered types of car (including saloon, batchback and estate cars). Sample data collected from video images, by means of an interactive tool, have been subjected to principal component analysis (PCA) to define a deformable model having 6 degrees of freedom. Secondly, a new pose refinement technique using “active” models is described, able to recover both the pose of a rigid object, and the structure of a deformable model; an assessment of its performance is examined in comparison with previously reported “passive” model-based techniques in the context of traffic surveillance. The new method is more stable, and requires fewer iterations, especially when the number of free parameters increases, but shows somewhat poorer convergence. Typical applications for this work include robot surveillance and navigation tasks.

Performance statistics of a head-operated force-reflecting rehabilitation robot system

Researchers in the rehabilitation engineering community have been designing and developing a variety of passive/active devices to help persons with limited upper extremity function to perform essential daily manipulations. Devices range from low-end tools such as head/mouth sticks to sophisticated robots using vision and speech input. While almost all of the high-end equipment developed to date relies on visual feedback alone to guide the user providing no tactile or proprioceptive cues, the “low-tech” head/mouth sticks deliver better “feel” because of the inherent force feedback through physical contact with the user's body. However, the disadvantage of a conventional head/mouth stick is that it can only function in a limited workspace and the performance is limited by the user's strength. It therefore seems reasonable to attempt to develop a system that exploits the advantages of the two approaches: the power and flexibility of robotic systems with the sensory feedback of a headstick. The system presented in this paper reflects the design philosophy stated above. This system contains a pair of master-slave robots with the master being operated by the user's head and the slave acting as a telestick. Described in this paper are the design, control strategies, implementation and performance evaluation of the head-controlled force-reflecting telestick system.