Fault tolerant, high availability navigation systems used in the oil and gas industry today can already be considered automated. However, there are always at least two people on watch on typical mobile offshore drilling unit (MODU) as the Dynamic Positioning systems still rely on human intervention to take action when automatic fault detection and decision making are defeated. Automatic station keeping of a MODU is currently limited to benign environments where the operation of other vessels within 500m is either forbidden or highly regulated. The project will address these limitations by delivering a step change in the level of automated positioning possible. The technology developed and demonstrated will enable a vessel to behave in a safe and predictable manner beyond the point at which existing systems revert to human control. This will include safe, predictable positioning in the event of a sensor failure (such as the denial of GNSS), and enhanced positioning to enable moving in a challenging and complex environment.

When operating around offshore platforms and infrastructure, vessels rely on multiple sensors of different technologies to provide information to their Dynamic Positioning (DP) systems, enabling them to approach and maintain position. Commercially available radar and laser local position reference sensors, installed on the majority of DP enabled vessels, are used to position the vessel relative to targets installed on the infrastructure. The use of targets presents a number of safety issues and cost implications including: safety concerns during installation; unreliability of reflections due to the poor quality of targets, interference from obstructions; maintenance and CAPEX costs; increased operational time and costs. Guidance Marine (GM) is a leading global developer and supplier of DP position measurement technologies. GM has developed a novel environmentally referenced sensor to enhance the safety and efficiency of global DP enabled operations at sea in response to industry concerns and direct mandate from oil majors. During this industrial research project, GM will develop a human-machine interface that ensures that outputs of this technology hide technical complexity to the end-user and allows maximal impact of the technological advance.

This project aims to bring collision avoidance technology to the marine market. Like a vehicle parking sensor, the SafeSurround concept aims to provide audio and visual alarms to warn ships’ officers of collision hazards. However, the technical challenges to achieve this are much greater than for a vehicle parking sensor, when the vehicle is a 90m-long vessel being buffeted by waves. The need for a hazard detection system has been raised by the Marine Safety Forum as a result of an increasing number of vessel collisions with offshore oil installations. This is partly because increased size and power of support vessels increases their capability to cause damage, and also because inexperienced crews are failing to adhere to safety procedures and guidance. In 2005 a support vessel collided with the Mumbai High North processing platform, causing a fire that resulted in 22 deaths, the destruction of the platform and $195m in lost revenue and clean-up costs. Guidance Marine Ltd (GML) is the leading developer and supplier of local position reference sensors for Dynamic Positioning (DP) and other vessel control systems. GML’s laser and radar sensors can be integrated by all major DP manufacturers and are used on a daily basis by most Offshore and Platform Supply Vessel operators. GML’s products accurately measure the relative position of the target in relation to the sensor to enable the vessel to hold position and operate safely in close proximity to an installation. SafeSurround is envisaged as the final piece of the DP jigsaw, giving close-range (<300m) relative position information for hazard detection to work alongside laser and microwave DP sensors. The ultimate goal is to integrate SafeSurround into DP systems, but first the concept must be proven as a stand-alone system. The project will test the positioning and configuration of sensors required to protect a vessel from collisions, in a range of environments from harbours to oil rigs to the open sea.

This project aims to prove the feasibility of producing a high impact advance in surveying of the railway network through the development of a novel device capable of high speed asset monitoring and automated asset identification for the railways. It is aimed to support the work of Network Rail and their sub-contractors who require detailed asset maps of the rail infrastructure. The project builds on recently patented IP from Oxford University Mobile Robotics Group. The combination of Laser Scanning and HD camera hardware will combine with satellite navigation systems to create a 3D topometrically correct asset map of the rail network which is automatically analysed with the latest visual analytics techniques. Trial units will be developed and outputs displayed.

Factory automation separates robots from operators. Developing soft robotics enables humans to work in close collaboration with Automated Mobile Robot’s (AMR’s), leveraging a humans full manipulative & decision-adaptive skills. Scheduling AMR movement in areas also occupied by humans provides a key component in this capability. The project requirement is driven by 10 yrs of massive growth in internet shopping that has had a huge impact on the assembly of small orders & with multi-channel selling has profoundly affected warehouse design. Order picking is usually the highest active cost element behind the passive cost of inventory. The need for efficiency & accuracy is driving the sector to various forms of pick automation. Industry experts expect future solutions to be vision guided, robotic piece picking & shuttles roaming a facility to make a delivery in an environment where automated materials handling, robotics & humans intermingle. This can only be fully realised if appropriate scheduling systems are developed. The 12 month project aims to prove the technical feasibility of a highly novel dynamic AMR scheduling solution, capable of optimising the schedule of a large fleet (>50) of AMR’s operating in a soft robotics environment. The project will develop the schedule control algorithms & demonstrate the feasibility in both a controlled work space & in a small representative end user trial. The scheduling solution will optimise the route of a large fleet of AMR’s so the time of travel for each order is minimised while its timed arrival at the picking locations minimises the distance walked between picking points by the operator, while also ensuring no vehicle collisions & minimum waiting times. Guidance has engaged with an innovative high growth distribution business to provide enduser insight & representative trial facilities & is utilising specific schedule algorithm expertise from the University of Birmingham School of Computer Science as sub-contractors.

The project aims to assess the feasibility of developing an ultra-low cost automated mobile robot (AMR) using infrastructure free navigation algorithms and very low cost vision systems for both navigation and obstacle detection. It is aimed to support more automated warehouse piece picking operations and will be deployed in an environment in which humans and robots continuously intermingle cooperatively. The project builds on recently patented IP from Oxford University Mobile Robotics group The project develops the specification and requirements for an AMR for use in the fast growth piece picking warehouse operations. The feasibility of using infrastructure free navigation algorithms and a very low cost commercial off the shelf vision system will be assessed. The use of the low cost vision system will also be reviewed for capability for combined navigation and obstacle detection. A trial AMR unit will be produced as a technology demonstrator and tested in a representative warehouse environment.

Many offshore vessels use GPS based Dynamic Positioning (DP) systems to assist navigation and control. New position measurement equipment (PME) classification society rules for DP vessels require that three independent PME are used during certain operations. The requirement for independence is based on common failure modes, so multiple GPS cannot be counted as independent. Currently close positioning of vessels in relation to offshore installations is undertaken with 2D laser or radar positioning systems working in conjunction with the vessels DP system, these provide x & y coordinates. Existing equipment relies on specialised targets, e.g. laser prism clusters on fixed offshore platforms, being correctly deployed and maintained prior to operational commencement to enable the identification of the relative location, see Fig 1. The targets need to be carefully positioned in order for existing systems to function correctly and reliably. Any problems tend to become apparent during the critical period before operations commence and occasionally during operations, due to external influences e.g. other vessels obscuring the line of sight required by existing equipment or false reflections from other mobile reflective devices. Fig 2 illustrates a typical system. See confirmation of issues from Swire Group one of the largest DP fleet operators in App A. Vessel positioning is also limited by the visibility of the targets in relation to the sensor location, constraining the angle of approach. This may hamper operational access in adverse weather conditions and also often leads to vessels queueing for access, adding significant operational costs. The location of targets is limited by available architecture and may not be optimally sited. There are significant set up and maintenance costs associated with these targets. The requirement for locating the reflectors on the platform also adds commercial complexities, in terms of installing, maintaining and liability. Locating the sensors is a particular challenge on unmanned installations. Existing systems provide a 2D planar view of the position and do not identify potential anomalies in the elevation field of view. The project aims to develop a multibeam laser sensing system that provides the derived 3D position from the laser image (see Fig 3 for example) for integration into the DP system to enable offshore operation without targets. It will increase operational flexibility, e.g. direction of approach, weather window, consequently allowing the owners to achieve higher lease and utilisation rates. It enables the identification of anomalies in x,y and z fields reducing the risk of collisions and subsequent costs, and improving safety. The positioning capability is selfcontained within the vessel. The flexibility is additionally interesting for more dynamic offshore installations such as offshore construction sites. It could also interface with other vessel control systems such as stability or crane control.