Opportunity to collaborate and help lead research on autonomous, perception-driven robot manipulation with a focus on combining machine learning with planning. Current tools we are interested in expanding our work on include learning with graph neural networks for multi-object and deformable manipulation and using tactile sensing to improve in-hand and post-grasp manipulation. Additionally interested in scaling up existing manipulation methods to handle longer-horizon planning and many hundreds to thousands of objects. Optionally opportunities exist to to mentor graduate students and get experience in writing and submitting research grant proposals.

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