My internship with the RoboClean team involved developing a custom Alexa skill to control Neato vacuum cleaners by voice. This will enable further development to link with the voice interface if required, as the other aspects of the project involve web systems and multi-agent systems. I also helped run a study to find out how users would interact with the potential system in a lab environment.
I enjoyed the work as it was in an area that interested me and had some challenges in the code to overcome, leading me to learn more about how the systems worked to explore different solutions. It was nice to be able to build on skills about Alexa development learnt in my 3rd year project and include linking to the neato API through HTTP requests and a 3rd party library. This included setting up the Account Linking on the Alexa skill and then adapting some of the code from libraries to work with node.js on the backend instead of front-end JS-based methods that were already in place.
Designing the interactions with the robot and the user was also very interesting as I wanted to make sure that the system would prompt for the necessary information about the robot, and location to clean, without becoming annoying for the user.
The internship will help with my studies and future work as it has given me experience of working with a research team, building on areas I had some experience in as well as expanding to other technical skills that I hadn’t used before, and will be useful in the future.
Written by Jane Slinger
I was introduced to the RoboClean project at Horizon whilst interning with the Advanced Data Analysis Centre. The project investigates the ways in which end-users interact with a robot vacuum cleaner and how a robot responds to user utterances; the aim being to inform its effective design and use within food factories.
I was invited to continue my internship for 5 more weeks within Horizon to help with the analysis of data collected through an elicitation study. Overall, this has been a really valuable and rewarding experience. Coming from an academic background in Sociology, I found working closely with researchers specialising in Computer Science exposed me to different research aims and challenges than I had previously encountered. This has been insightful for me as it has not only helped develop new skills in research analysis and interview techniques, but also applied the principles of a range of research methods gained during my academic studies over the past 2-years to cutting edge technological developments.
I have been responsible for transcribing participants’ audio data, analysing visual data, and creating a summary written report of participants’ interview responses. The focus of the report was on the benefits, limitations, and disadvantages experienced by users from the user-robot interactions. The attendance at a range of team meetings has also been beneficial in understanding interactions within a work environment, especially where individuals are working together from across a range of disciplines. Combined with the skills I have learned at workload prioritisation and management, this has made me confident to face future work situations and dilemmas. Additionally, I have written literature reviews on the topic of human-robot interaction. Being able to explore these new topics has also helped me see how issues explored in Sociology are becoming increasingly influenced by the world of technology, for example, how individuals’ day-to-day lives are mediated by the introduction of robots to the workplace. The multidisciplinary projects throughout Horizon have therefore also been interesting to work alongside, clearly showing the benefit of collaborative projects in producing innovative findings.
Contributing to a research project which is aiming for publication in a research journal has been hugely rewarding and exciting, and has made the idea of working in a similar environment after graduating a lot more persuasive.
Written by Charlotte Gray
In collaboration with the AI3 Science Discovery (AI3SD) and Internet of Food Things (IoFT) EPSRC Networks the RoboClean team ran a workshop in London on the 17th of October. The focus of the workshop was to discuss how digital technologies such as AI, sensors and robotics can be used for enhanced allergen detection and factory cleaning within food production environments. The workshop was well attended by a range of stakeholders from industry, academia and organisations such as the Food Standards Agency. The morning of the workshop had three speakers. Nik Watson from the University of Nottingham gave a talk on the future of factory cleaning. This talk covered a range of research projects from the University which developed new digital technologies to monitor and improve factory cleaning processes. The second talk was from AI3SD lead Jeremy Frey from the University of Southampton. Jeremy’s talk gave an introduction to AI and covered a range of new sensors which could be used to detect the presence of allergens in a variety of food products and environments. The final talk was delivered by Martin Peacock from Zimmer and Peacock, a company who develop and manufacture electrochemical sensors. Martin gave an introduction to the company and the technologies they develop before demonstrating how there sensor could be connected to an iPhone and determine the hotness of chilli sauce. Martin’s talk finished by discussing how electro chemical sensors could be used to detect allergens within a factory environment. The afternoon of the workshop focused on group discussions on the following the four topics – all related to allergen detection and cleaning within food production:
- Data collection, analysis and use
- Ethical issues
- Cleaning robots
Each group had a lead, however delegates moved between tables so they could contribute to more than one discussion. At the end of the workshop the lead from each group reported back with the main discussion points covered by the delegates. The delegates on the ‘robotics’ table reported that robots would play a large role in the future of factory cleaning as they would free up factory operators to spend time on more complicated tasks. The group felt that the design of the robots was essential and discussed that new factories should also be designed differently to facilitate robot cleaning more easily. The group also thought that effective communication with the robot was a key issue which needed further research. The ‘sensors’ group reported that any new sensors used to detect allergens or levels of cleanliness would need to fit into existing regulations and practices, but would be welcomed by the industry, especially if they could detect allergens or bacteria in real-time. The ‘data’ group reported that there was a need for data standards relevant to industrial challenge and there was also a need for open access data to enable the development of suitable analysis and visualisation methods. The ‘ethics’ group discussed numerous key topics including, Bias, Uncertainty, transparency, augmented intelligence and the objectivity of AI.