Generative modelling for robot locomotion and manipulation

对研究背景的简要描述，包括潜在的影响：深度生成模式是表征学习的一个越来越受欢迎的选择。我博士的目标是将这些方法应用于机器人学。这些模型已经显示出允许机器人在以对象为中心的水平上对其环境进行推理的潜力。这意味着机器人将能够与他们的环境自然互动。我正在研究腿部机器人的移动和机械臂的操作。我的研究的影响将是允许腿部机器人在对人类来说太危险的环境中执行搜救或检查任务。应用于机械臂的工作将对从医疗保健到制造和仓储等领域产生影响。目的和目的这项研究的目的是改进机器人的交互方式，并对它们工作的环境进行推理。目标是让机器人执行人类认为理所当然的任务，比如能够将精致的物体装进装运箱或在崎岖的地面上行走。研究方法的新颖性目前允许机器人与环境互动的技术严重依赖于仅对非常特定的场景有效的假设。生成性模型使它们所训练的所有数据合理化。这是这些模型应用于机器人时非常有吸引力的特性。与EPSRC的战略和研究领域保持一致这个项目直接属于EPSRC机器人学和人工智能研究领域。要让机器人解决错综复杂的问题并对其环境进行推理，需要对机器学习进行研究，以创造某种人工智能。

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 ObjectivesThe 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 methodologyCurrent 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 areasThis 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.