Optimising remote handling telepresence systems through studying how users adapt to altered sensory motor contingencies.

We are constantly adapting to and learning about the environment we live in. This can occur over different time spans for everyone for example, a child learning to walk can take anywhere from 9 months to 18 (https://health.clevelandclinic.org/when-do-babies-start-walking). We are also constantly learning and adapting to new things throughout our lives from how to play different sports and games, to wearing new glasses.

These may seem easy for some but others can find it difficult to adapt to different rules or a new environment around them. In all of these cases the adaptation and learning requires the brain to be open to the changes and understand the new ways there are to react.

These processes have been extensively studied throughout Psychology so that we can understand how we process different information in order to make it easier for us to adapt. However most of this has been studied in a simple fashion by watching different people and making notes. As technology has developed it is now within our capabilities to track movements and collect a range of data that we did not have access to before.

This will allow us to address more complicated tasks that occur regularly in the real word for example, how a person uses a computer mouse vs a track pad. These two do the same job, but can have varying degrees of difficulty depending on a person's spatial awareness or motor capabilities.

It is critical to be able to understand how a person learns and adapts so we can better training exercises and optimise them to work in, for example, an industrial setting. There are currently numerous examples of this already going on through telepresence, robot assisted surgery, bomb disposal, and more.

Nuclear fusion is becoming increasing popular as we move further away from fossil fuels to more renewable energy that is better for the environment. It is also safer and can be used on an industrial scale. This technology will transform the way society works whilst allowing us to adapt with our environment to reduce climate change.

In order to achieve this, we will need to have good telepresence operations so that machines can be properly looked after and the training required for it is optimised for better learning. If this isn't the case it can cause high costs and time can be lost from simply having to learn how to use the machinery. In some cases people wont be able to adapt to this as they simply will not be able to complete the tasks.

There is still a lot of improvement to be made in this field and it is our hope to address this gap by starting the process of understanding and changing the way people are trained for better optimisation and learning.

The research that we are completing is inherently multidisciplinary as applies rigorous experimental methods to real world industrial settings, like at RACE who develop remotely-operated and autonomous machines to inspect, maintain and upgrade machines in challenging environments (https://race.ukaea.uk/). It also builds on my previous experiences of biomedical engineering through the use of haptic technology and virtual environments.

This will also further the research I completed as part of my dissertation where I worked in a psychology lab to understand how movement can be tracked and manipulated to aid people in completing tasks.

All of these processes require us to understand how the brain process sensory information, so that the what we learn can be used to solve different problems and allow people the correct training to properly understand how to use the machinery or adapt to the environment. By tracking movement and other such data it will allow us also to see where errors occur whilst using specific machinery and how these can be reduced (Lopez Pulgarin et al., 2022).