University of Edinburgh
There is significant interest in characterising surgical skills in the form of detailed models that correlate hand movements, applied forces and the context of the shape and texture of tissues that are actually being manipulated.
Objects play a central role in the behaviour of intelligent systems like robots. This makes semantic object segmentation a fundamental basic component of many applications. State-of-the-art object segmentation is often done training expensive networks with lots of labelled images. This means that new knowledge is expensive to acquire, since the network needs lots of labelled images of each new object. In addition, these networks take as input only single images, ignoring all the useful information from the motion of objects.
The ignition of flammable liquids and gases in offshore oil and gas environments is a major risk and can cause loss of life, serious injury, and significant damage to infrastructure. Power supplies that are used to provide regulated voltages to drive motors, relays, and power electronic controls can produce heat and cause sparks. As a result, the European Union requires ATEX certification on electrical equipment to ensure safety in such extreme environments. Implementing designs that meet this standard is time-consuming and adds to the cost of operations.
Operations in hostile environments–such as those found in Nuclear Decommissioning, Oil and Gas, Mining, and Space–require the execution of sophisticated tasks. Examples of these tasks are: building structures, and deploying tools for inspection, lifting, and cutting. These environments pose a significant risk to the health and safety of manual workers. The safety of personnel can be mitigated by the use of autonomous robotic systems which can perform the required tasks in these extreme environments.
These environments present the following challenges: