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Describes the current research into vision‐based control of remotely controlled vehicles. The research at Robotics and Mechatronics Research Laboratory (RMRL), Monash University, Australia, aims to establish the foundation for future studies in control actions on levers and joysticks for guiding remotely operated vehicles. Use is made of a remote‐controlled car which is tracked by an overhead camera. A frame grabber is utilized to process the images and pass the necessary information about the relative position of the vehicle to the computer. Two servo‐driven mechanical arms are controlled to move the joysticks on the remote control unit. Focuses attention on simplified strategies for tracking and the subsequent control of such vehicles. Describes experimental facility comprising of the mechatronic components and their integration within this research‐based apparatus. Also presents future work in this area.

The purpose of this study is to develop a new positioning method for remotely operated vehicle (ROV) in the nuclear power plant. The ROV of the nuclear power plant is developed to inspect the reactor cavity pools, the component pools and spent-fuel storage pools. To enhance the operational safety, the ability of localizing the ROV is indispensable.

Therefore, the positioning method is proposed based on the MEMS inertial measurement unit and mechanical scanning sonar in this paper. Firstly, the ROV model and on board sensors are introduced in detail. Then the sensor-based Kalman filter is deduced for attitude estimation. After that, the positioning method is proposed that divided into static positioning and dynamic positioning. The improved iterative closest point-Kalman filter is deduced to estimate the global position by the whole circle scanning sonar data in static, and the relative positioning method is proposed by the small scale scanning sonar data in dynamic.

The performance of the proposed method is verified by comparing with the visual positioning system. Finally, the effectiveness of the proposed method is proved by the experiment in the reactor simulation pool of the Daya Bay Nuclear Power Plant.

The research content of this manuscript is aimed at the specific application needs of nuclear power plants and has high theoretical significance and application value.

UAVs or unmanned (or the more politically correct, “unpiloted” or “uninhabited”) Aerial Vehicles and the broader class of remotely operated vehicles (ROVs) have attracted much attention lately from the military, as well as the general public. Generally, ROVs are vehicles that do not carry human pilots or operators, but instead are controlled remotely with different degrees of autonomy on the part of the vehicle. The role of UAVs in the military has rapidly expanded over the years such that every branch of the U.S. military deploys some form of UAV in their intelligence, surveillance, and reconnaissance operations. Recent U.S. military successes include a USAF Predator UAV operating in Iraq, but piloted by a team at Nellis AFB (now Creech AFB) in Las Vegas, Nevada, which successfully aided in finding Saddam Hussein (Rogers, 2004). Another more recent example took place in August 2004 when a Predator UAV armed with Hellfire missiles, also controlled from Nellis AFB, rescued a group of U.S. Marines pinned down by sniper fire in Najaf, Iraq (CNN, 2005). The value of UAVs is recognized by other nations as well who have active UAV programs including, but not limited to, Germany, England, China, France, Canada, South Africa, and Israel.

SA has been described as “generating purposeful behavior.” that is, behavior that is directed toward a task goal (Smith & Hancock, 1995). It involves being aware of what is happening around you and understanding what occurring events mean with respect to your current and future goals. Endsley (1995) has formally defined SA as the “perception of elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future” (Endsley, 1995, p. 36). SA has been hypothesized as being critical to operator task performance in complex and dynamic operations (Salas, Prince, Barker, & Shrestha, 1995), like tasking and controlling remotely operated systems. Operators in remote control of ground vehicles need to be aware of where the vehicle is, what the vehicle is doing, and how activities as part of the overall task lead to accomplishment of mission goals. They must also consider the health of the overall system and how the environment affects vehicle status and the ability to complete tasks. In studying robot control in simulated USAR operations, Drury, Scholtz, and Yanco (2003) observed that most of the problems encountered when navigating robots resulted from the human's lack of awareness of these elements.

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 aims to provide details of underwater robot technology and its applications.

Following an introduction, this article first discusses remotely operated vehicle (ROV) technology and applications and then considers their use in the emerging field of deep-sea mining. It then discusses autonomous underwater vehicle (AUV) technology and its applications, including sub-sea gliders. Finally, brief concluding comments are drawn.

ROVs were first developed in the 1950s for military applications. They are now widely used by the offshore oil and gas sector and other industries and are being developed for deep-sea mining. AUV technology has progressed rapidly in recent years and AUVs, including sub-sea gliders, are now emerging from their original role in oceanographic research and finding growing uses in the defence and offshore energy sectors.

This provides a detailed insight into underwater robot technologies, products and applications.

The great success of unmanned aerial vehicles (UAVs) in performing near-real time tactical, reconnaissance, intelligence, surveillance and other various missions has attracted broad attention from military and civilian communities. A critical contribution to the increase and extension of UAV applications, resides in the separation of pilot and vehicle allowing the operator to avoid dangerous and harmful situations. However, this apparent benefit has the potential to lead to problems when the role of humans in remotely operating “unmanned” vehicles is not considered. Although, UAVs do not carry humans onboard, they do require human control and maintenance. To control UAVs, skilled and coordinated work of operators on the ground is required.