This project will investigate how such human-robot collaborative tasks can be carried out, concentrating on the communication aspects: how the robot communicates its intentions to the human, and how the human can query and interact with the robot's plan. The research will be driven by oilfield drilling applications, which involve control of complex equipment in a dynamic environment, with an increasing level of automation. Close coordination between the human crew and the automation system is often required, as is building trust between the human and the machine so that the crew understand why the machine acts the way it does and is confident it has taken all available information into account. The project is an EPSRC iCASE award with Schlumberger Gould Research and it is expected that the student will spend some time working with the company in Cambridge.
The student should have excellent experience, enthusiasm and skills in the areas of natural language or multimodal interaction and/or automated planning and reasoning. Applicants must hold a good Bachelor's or Master's degree in a relevant discipline.
In this PhD project, the student will investigate how advanced techniques drawn from natural language generation (NLG) can be combined with practical social robotics applications. The success of the integration will be evaluated through a combination of subjective user evaluations of the social robots as well as technical evaluations of the flexibility and robustness of the underlying systems. In addition to the scientific results of the PhD, an additional goal is to produce a reusable, open-source component for NLG in the context of social robotics, to allow other researchers in this area to benefit from the results of the research.
The PhD student should have excellent experience, enthusiasm and skills in the areas of natural language processing, computational linguistics, multimodal interaction, and/or human-robot interaction. Applicants must hold a good Bachelor's or Master's degree in a relevant discipline.