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At The Robot Learning Lab, we are developing advanced robots that are empowered by artificial intelligence, for assisting us all in everyday environments. Our research lies at the intersection of robotics, computer vision, and machine learning, and we are primarily studying robot manipulation: robots that can learn to physically interact with objects using their arms and hands. Applications include domestic robots (e.g. tidying the home), manufacturing robots (e.g. assembling products in a factory), and warehouse robots (e.g. picking and placing from/into storage). The lab is led by Dr Edward Johns in the Department of Computing at Imperial College London. Welcome!
Two papers published at CoRL 2023!
We show that, by deforming random objects in simulation, we can easily generate a large set of virtual demonstrations for tasks requiring generalisation across object shapes. This diverse training data then allows us to predict the quality of a test alignment of objects when conditioned on demonstration alignments, hence achieving few-shot in-context imitation learning.
We study a novel combination of trajectory transfer and unseen object pose estimation, which enables new tasks to be learned from just a single demonstration, without requiring any further data collection or training. Under this formulation, experiments provide a deep dive into the effects of pose estimation errors and camera calibration errors on task success rates.
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