Generative modelling for robot locomotion and manipulation

Brief description of the context of the research including potential impact:
Deep generative models are increasingly a popular choice for representation learning. The aim of my PhD is to apply these methods to robotics. These models have shown the potential to allow robots to reason about their environments at an object-centric level. This means that robots will be able to interact naturally with their environment.

I am working on legged robot locomotion and manipulation of robotic arms. The impact of my research will be to allow legged robots to perform search and rescue or inspection tasks in environments too dangerous for humans. Work applied to robot arms will have an impact in areas from health care to manufacturing and warehousing.

Aims and Objectives
The aim of this research is to improve how robots interact and reason about the environments they work in. The objectives are to have robots perform tasks that humans take for granted, such as being able to pack delicate objects into a shipping box or walking over rough terrain.

Novelty of the research methodology
Current techniques which allow robots to interact with their environments heavily rely on assumptions which are only valid for very specific scenarios. Generative models rationalise over all the data that they are trained on. This is a very attractive property of these models when applied to robotics.

Alignment to EPSRC's strategies and research areas
This project falls directly into both the EPSRC robotics and artificial intelligence research areas. To have robots solve intricate problems and reason about their environments requires research into machine learning to create some sort of artificial intelligence.

The UK is faced with an increasing skills shortage, with a recent (2012) large-scale survey reporting that half of all key UK industries surveyed suffer from a worsening skills shortage. This is even more acute in high-tech industry and requires core investment in teaching highly-qualified cohorts, not only the foundational theoretical underpinning in this CDT's remit, but also the acumen to bring this theory to bear on a range of real problems. This CDT will promote training in transformative research that will revolutionise and intertwine theory and practice. If we are to train a generation of researchers to lead in the use of pervasive computation we must actively promote interconnecting research areas. The CDT directly addresses the Autonomous Systems & Robotics priority area and interlinks with priorities in Digitally Connected Citizens, New Digital Ventures, and smart Energy Systems and Digital Healthcare. Furthermore, the CDT has strong links to several current EPSRC challenge themes: 1) Manufacturing the Future: Sustainable manufacturing can only be achieved via autonomy, and machine intelligence at global scale. In today's market, the UK's competitive advantage lies in training highly-skilled researchers that will be able to pioneer distributed autonomous systems into manufacturing processes. 2) Energy: Intelligence and autonomy are key to energy-efficient driving and transportation systems, smart energy grids and efficient use of sparse resources. 3) Digital Economy: Intelligent machines and systems can assist people and give them control over their lives in a number of contexts, such as assisted living, home healthcare, transportation, skill & knowledge transfer and telepresence. 4) Living with Environmental Change: Intelligent hand-held devices and participatory sensing will extend environmental monitoring to unprecedented spatial and temporal scales, building real sensor systems and citizen science platforms to monitor the environment, pollutants and biodiversity.

The CDT will allow us to bring together our collaborations with industrial partners into a unique consortium, which will underpin the student training program, from fundamentals to development, deployment and use. The CDT has secured support not only from the University, but also from a team of industrial partners, who share our vision. We have support from an impressive list of companies, from global multi-nationals and large corporations, such as BAE Systems, BP, Schlumberger & YouGov (internships, studentships and membership of the external steering group), Microsoft, Google, Honeywell, Ascending Technologies, SciSys & Man Group (internships & part of our external steering group), ABB, Infosys, QinetiQ (internships and studentships). Industry and commerce will have an active participation in the CDT programme via internships and studentships; provision of short lectures highlighting the practical application of the taught material; proposing first-year research projects; membership of the steering committee; industrial placements into Oxford. Industrial participation, at all levels, will enhance the quality of the training programme and provide access to a unique pool of CDT talent. We believe that our approach to industrial engagement places realistic requirements on both industry and students.

The benefits of the CDT will be many-fold. The students will benefit via a strong foundation in the principles & practice of autonomous & intelligent systems and subsequent research with world-leading groups. The enthusiasm shown by a range of industries indicates an appetite for engaging with the student cohort, promoting clear dissemination, impact and collaboration routes benefiting industry, academia and the UK economy.