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Applied Artificial Intelligence Lab (A2I)

A2I group photo.

The Applied AI Lab (A2I) explores core challenges in AI and Machine Learning to enable robots to robustly and effectively operate in complex, real-world environments. Our research is guided by our vision to create machines which constantly improve through use in their dedicated workspace. In doing so we explore a number of intellectual challenges at the heart of robot learning such as machine introspection in perception and decision making, data efficient learning from demonstration, task-based and transfer learning and the learning of complex tasks via a curriculum of less complex ones. All the while our intellectual curiosity remains grounded in real-world robotics domains such as autonomous driving, logistics, manipulation or space exploration.

RT @omgroth: Looking forward to presenting our latest work on goal-conditioned visuomotor control today at #ICRA2021! 😃 Joint work with @ch

Code for our recent paper on Genesis-V2 is now on GitHub! arxiv: https://t.co/9jw3qxAuWk code: https://t.co/43wkEcPC4k https://t.co/1w84kEsq9Z

RT @IngmarPosner: This is special. Truly delighted to have been part of this team. https://t.co/thAIqNTl68

RT @martinengelcke: "GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement" #tweeprint TL;DR: Unsupervised o…

RT @IngmarPosner: Hugely excited to be leading this with so many great partners and colleagues involved. Starting 2021... @a2i_oxford @oxfo

RT @Alex_L_Mitchell: Interested in solving for locomotion trajectories for complex real-world robots? We find solutions via gradient descen…