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This paper aims to provide details of recent developments in robots aimed at applications in the offshore oil and gas industries.

Following a short introduction, this first discusses developments to remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs). It then describes the Total-sponsored Autonomous Robot for Gas and Oil Sites (ARGOS) robot challenge. This is followed by a discussion of the Offshore Robotics for Certification of Assets (ORCA) programme. Finally, brief concluding comments are drawn.

Subsea residency and other techniques are being developed that will enhance the availability and capabilities of AUVs and ROVs and reduce their operating costs. Mobile robots that can operate in harsh topside rig environments to monitor and detect hazards arose from ARGOS and are being developed further prior to commercialisation. Bringing together academics and users, the collaborative ORCA programme is making significant progress in the development of aerial, topside and underwater robotic and sensing technologies for rig asset inspection and maintenance.

This paper identifies and describes key development activities that will stimulate the use of robots by the offshore industries.

This paper investigates developing a learning-to-learn capability as a critical success factor for sustainable lean transformation.

This research design is guided by our research question: how can suppliers learn to learn as part of a buyer-led collaborative lean transformation? The authors adopt action learning research to generate actionable knowledge from a lean supplier development initiative over a three-year period.

Drawing on emergent insights from the initiative, the authors find that developing a learning-to-learn capability is a core and critical success factor for lean transformation. The authors also find that network action learning has a significant enabling role in buyer-led collaborative lean transformations.

The authors contribute to lean theory and practice by making the distinction between learning about and implementing lean best practices and adopting a learning-to-learn perspective to build organisational capabilities, consistent with lean thinking and practice. Further, the authors contribute to methodology, adopting action learning research to explore learning-to-learn as a critical success factor for sustainable lean transformation.

Advanced Robotics Research Ltd (ARRL) launched their Virtual Reality and Simulation Initiative at the National Advanced Robotics Research Centre, Salford, on Friday, 2 July 1993. Lord Wade of Chorlton was the Guest of Honour.

Looks at Amadeus (advanced manipulator for deep underwater systems) which is an international subsea manipulator project, funded by the European Community Marine Science and Technology Research Programme. The object is to improve the sampling and manipulation capabilities of underwater systems, through the development of advanced grippers and manipulation control techniques. Says that Phase 1 of the project produced an innovative dextrous gripper system for laboratory use. The objective of phase 2 is to produce more robust systems offering enhanced functionality and suitability for trials in the marine environment. Provides an overview of the Amadeus project describing the achievements of the first phase and the proposed developments for phase 2.

Laser imaging and ranging systems offer 3‐D imaging of video quality at distances four to five times greater than conventional video and photographic systems. The Spotmap system is based on the laser radar approach, using a pulsed green solid state laser as a transmitter and detecting the time‐of‐flight and peak intensity of the reflected pulses. Images and maps of underwater scenes are obtained by scanning the laser beam across the objects in a raster pattern using a two‐axis optical scanner. The system can be used both in linescan and 2D scan modes of operation such that images can be obtained either from the linear movement of the remotely operated vehicle or from a stationary position. The system has a 90∞ cross‐track FOV and is capable of processing 8,000 points per second, which gives an imaging resolution comparable to video at ROV speeds up to 2m/s.

SILVER, the special interest group on advanced robotics and intelligent automation, is holding a series of meetings on applications in different sectors of industry. The May meeting was held at the Silsoe Research Institute in Bedfordshire. Speakers from Silsoe, as well as from universities and industry, reviewed a number of applications, current and potential, and some systems were demonstrated during the lunch break.