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A new type of high‐level robot command library is presented, which can be viewed as a marriage between simulation and control. The library commands contain simulations of the physical abilities of the robots as well as having the ability to control the physical machinery. The control of the machinery is performed by translating parameter information and then mapping the library commands to the robot controller commands. To demonstrate the use of the libraries, two robot programming languages have been analysed and new robot command libraries created for two types of machine. The robots selected were a Fanuc A600 and a Unimation PUMA robot. The paper also presents criteria that were used for assessing programming languages for use in programming and controlling robots. The paper shows how simulation can be incorporated into a high‐level robot command library (or object library) and how the command library can be used for the programming of industrial robots. The work has demonstated the advantages of including simulation within robot command libraries. The purpose of the research has not been to define another new robot command library, and the techniques presented here can be applied to other robot languages and high level robot command libraries.

Describes a new reliable low‐cost ultrasonic ranging system to assist in steering a powered wheelchair. Detection algorithms have been created and implemented on a micro controller based stand‐alone system suitable for a tele‐operated vehicle. The detection uses the gradient of the echo envelope and is resistant to noise and inconsistencies in the detection circuitry. The sensor array was considered as separate sensors, working independently so the system could quickly gather separate sets of range information. These sets were overlaid on to a 2D grid array. The new system is cheaper and simpler than available systems for powered wheelchairs.

The purpose of this paper is to investigate how to make tele‐operated tasks easier using an expert system to interpret joystick and sensor data.

Current tele‐operated systems tend to rely heavily on visual feedback and experienced operators. Simple expert systems improve the interaction between an operator and a tele‐operated mobile‐robot using ultrasonic sensors. Systems identify potentially hazardous situations and recommend safe courses of action. Because pairs of tests and results took place, it was possible to use a paired‐samples statistical test.

Results are presented from a series of timed tasks completed by tele‐operators using a joystick to control a mobile‐robot via an umbilical cable. Tele‐operators completed tests both with and without sensors and with and without the new expert system and using a recently published system to compare results. The t‐test was used to compare the means of the samples in the results.

Time taken to complete a tele‐operated task with a mobile‐robot partly depends on how a human operator interacts with the mobile‐robot. Information about the environment was restricted and more effective control of the mobile‐robot could have been achieved if more information about the environment had been available, especially in tight spaces. With more information available for analysis, the central processor could have had tighter control of robot movements. Simple joysticks were used for the test and they could be replaced by more complicated haptic devices. Finally, each individual set of tests was not necessarily statistically significant so that caution was required before generalising the results.

The new systems described here consistently performed tasks more quickly than simple tele‐operated systems with or without sensors to assist. The paper also suggests that the amount of sensor support should be varied depending on circumstances. The paired samples test was used because people (tele‐operators) were inherently variable. Pairing removed much of that random variability. When results were analysed using a paired‐samples statistical test then results were statistically significant. The new systems described in this paper were significantly better at p<0.05 (95 per cent probability that this result would not occur by chance alone).

The paper shows that the new system performed every test faster on average than a recently published system used to compare the results.

The paper aims to propose a system that uses a combination of techniques to suggest weld requirements for ships parts. These suggestions are evaluated, decisions are made and then weld parameters are sent to a program generator.

A pattern recognition system recognizes shipbuilding parts using shape contour information. Fourier‐descriptors provide information and neural networks make decisions about shapes.

The system has distinguished between various parts and programs have been generated so that the methods have proved to be valid approaches.

The new system used a rudimentary curvature metric that measured Euclidean distance between two points in a window but the improved accuracy and ease of implementation can benefit other applications concerning curve approximation, node tracing, and image processing, but especially in identifying images of manufactured parts with distinct corners.

A new proposed system has been presented that uses image processing techniques in combination with a computer‐aided design model to provide information to a multi‐intelligent decision module. This module will use different criteria to determine a best weld path. Once the weld path has been determined then the program generator and post‐processor can be used to send a compatible program to the robot controller. The progress so far is described.

The purpose of this paper is to investigate the effect on completion of mobile‐robot tasks depending on how a human tele‐operator interacts with a sensor system and a mobile‐robot.

Interaction is investigated using two mobile‐robot systems, three different ways of interacting with the robots and several different environments of increasing complexity. In each case, the operation is investigated with and without sensor systems to assist an operator to move a robot through narrower and narrower gaps and in completing progressively more complicated driving tasks. Tele‐operators used a joystick and either watched the robot while operating it, or sat at a computer and viewed scenes remotely on a screen. Cameras are either mounted on the robot to view the space ahead of the robot or mounted remotely so that they viewed both the environment and robot. Every test is compared with sensor systems engaged and with them disconnected.

A main conclusion is that human tele‐operators perform better without the assistance of sensor systems in simple environments and in those cases it may be better to switch‐off the sensor systems or reduce their effect. In addition, tele‐operators sometimes performed better with a camera mounted on the robot compared with pre‐mounted cameras observing the environment (but that depended on tasks being performed).

Tele‐operators completed tests both with and without sensors. One robot system used an umbilical cable and one used a radio link.

The paper quantifies the difference between tele‐operation control and sensor‐assisted control when a robot passes through narrow passages. This could be an useful information when system designers decide if a system should be tele‐operated, automatic or sensor‐assisted. The paper suggests that in simple environments then the amount of sensor support should be small but in more complicated environments then more sensor support needs to be provided.

The paper investigates the effect of completing mobile‐robot tasks depending on whether a human tele‐operator uses a sensor system or not and how they interact with the sensor system and the mobile‐robot. The paper presents the results from investigations using two mobile‐robot systems, three different ways of interacting with the robots and several different environments of increasing complexity. The change in the ability of a human operator to complete progressively more complicated driving tasks with and without a sensor system is presented and the human tele‐operators performed better without the assistance of sensor systems in simple environments.

This paper aims to describe the creation of innovative and intelligent systems to optimise energy efficiency in manufacturing. The systems monitor energy consumption using ambient intelligence (AmI) and knowledge management (KM) technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems.

Energy consumption data (ECD) are processed within a service-oriented architecture-based platform. The platform provides condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase and continuous improvement/optimisation of energy efficiency. The systems monitor energy consumption using AmI and KM technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems.

The systems produce an improvement in energy efficiency in manufacturing small- and medium-sized enterprises (SMEs). The systems provide more comprehensive information about energy use and some knowledge-based support.

Prototype systems were trialled in a manufacturing company that produces mooring chains for the offshore oil and gas industry, an energy intensive manufacturing operation. The paper describes a case study involving energy-intensive processes that addressed different manufacturing concepts and involved the manufacture of mooring chains for offshore platforms. The system was developed to support online detection of energy efficiency problems.

Energy efficiency can be optimised in assembly and manufacturing processes. The systems produce an improvement in energy efficiency in manufacturing SMEs. The systems provide more comprehensive information about energy use and some knowledge-based support.

This research addresses two of the most critical problems in energy management in industrial production technologies: how to efficiently and promptly acquire and provide information online for optimising energy consumption and how to effectively use such knowledge to support decision making.

This research was inspired by the need for industry to have effective tools for energy efficiency, and that opportunities for industry to take up energy efficiency measures are mostly not carried out. The research combined AmI and KM technologies and involved new uses of sensors, including wireless intelligent sensor networks, to measure environment parameters and conditions as well as to process performance and behaviour aspects, such as material flow using smart tags in highly flexible manufacturing or temperature distribution over machines. The information obtained could be correlated with standard ECD to monitor energy efficiency and identify problems. The new approach can provide effective ways to collect more information to give a new insight into energy consumption within a manufacturing system.

The purpose of this paper is to investigate how to make powered‐wheelchair driving easier using simple expert systems to interpret joystick and ultrasonic sensor data. The expert systems interpret shaky joystick movement and identify potentially hazardous situations and then recommend safe courses of action.

The way that a human user interacts with a powered‐wheelchair is investigated. Some simple expert systems are presented that interpret hand tremor and provide joystick position signals for an ultrasonic sensor system. Results are presented from a series of timed tasks completed by users using a joystick to control a powered‐wheelchair. Effect on the efficiency of driving a powered‐wheelchair is measured using the times to drive through progressively more complicated courses. Drivers completed tests both with and without sensors and the most recently published systems are used to compare results.

The new expert systems consistently out‐performed the most recently published systems. A minor secondary result was that in simple environments, wheelchair drivers tended to perform better without any sensor system to assist them but in more complicated environments then they performed better with the sensor systems.

The time taken for a powered‐wheelchair to move from one place to another partly depends on how a human user interacts with the powered‐wheelchair. Wheelchair driving relies heavily on visual feedback and the experience of the drivers. Although attempts were made to remove variation in skill levels by using sets of data associated with each driver and then using paired statistical tests on those sets, some variation must still be present.

The paper presents new systems that could allow more people to use powered‐wheelchairs and also suggests that the amount of sensor support should be varied depending on circumstances.

The new systems described in the paper consistently performed driving tasks more quickly than the most recently published systems.

The purpose of this paper is to describe the use of simple expert systems to improve the performance of tele‐operated mobile robots and ultrasonic sensor systems. The expert systems interpret data from the joystick and sensors and identify potentially hazardous situations and then recommend safe courses of action so that tele‐operated mobile‐robot tasks can be completed more quickly.

The speed of a tele‐operator in completing progressively more complicated driving tasks is investigated while using a simple expert system. Tele‐operators were timed completing a series of tasks using a joystick to control a mobile robot through a simple expert system that assisted them with driving the robot while using ultrasonic sensors to avoid obstacles. They either watched the robot while operating it or sat at a computer and viewed scenes remotely on a screen from a camera mounted on the robot. Tele‐operators completed tests with the simple expert system and the sensors connected. The system used an umbilical cable to connect to the robot.

The simple expert systems consistently performed faster than the other systems. Results are compared with the most recently published results and show a significant improvement. In addition, in simple environments, tele‐operators performed better without a sensor system to assist them but in more complicated environments than tele‐operators performed better with the sensor systems to assist.

Simple expert systems are shown to improve the operation of a tele‐operated mobile robot with an obstacle avoidance systems fitted.

Tele‐operated systems rely heavily on visual feedback and experienced operators. This paper investigates how to make tasks easier. Simple expert systems are shown to improve the operation of a tele‐operated mobile robot. The paper also suggests that the amount of sensor support should be varied depending on circumstances.

The simple expert systems are shown in this paper to improve the operation of a tele‐operated mobile robot. Tele‐operators completed tests with the simple expert system and the sensors connected. The results are compared with a tele‐operator driving a mobile robot without any assistance from the expert systems or sensors and they show a significant improvement.

This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation.

A novel approach is taken to energy consumption monitoring by using ambient intelligence (AmI), extended data sets and knowledge management (KM) technologies. These are combined to create a decision support system as an innovative add-on to currently used energy management systems. Standard energy consumption data are complemented by information from AmI systems from both environment-ambient and process ambient sources and processed within a service-oriented-architecture-based platform. The new platform allows for building of different energy efficiency software services using measured and processed data. Four were selected for the system prototypes: condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase, and continuous improvement/optimisation of energy efficiency.

An innovative and intelligent solution for energy efficiency optimisation is demonstrated in two typical manufacturing companies, within one case study. Energy efficiency is improved and the novel approach using AmI with KM technologies is shown to work well as an add-on to currently used energy management systems.

The decision support systems are only at the prototype stage. These systems improved on existing energy management systems. The system functionalities have only been trialled in two manufacturing companies (the one case study is described).

A decision support system has been created as an innovative add-on to currently used energy management systems and energy efficiency software services are developed as the front end of the system. Energy efficiency is improved.

For the first time, research work has moved into industry to optimise energy efficiency using AmI, extended data sets and KM technologies. An AmI monitoring system for energy consumption is presented that is intended for use in manufacturing companies to provide comprehensive information about energy use, and knowledge-based support for improvements in energy efficiency. The services interactively provide suggestions for appropriate actions for energy problem elimination and energy efficiency increase. The system functionalities were trialled in two typical manufacturing companies, within one case study described in the paper.