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Thesis

Multi-task generalization for robotics

Abstract:

While robots that follow hard-coded instructions have been widely applied in the real world, learning intelligent robots that can autonomously accomplish different tasks in unstructured environments with unforeseen variations remains a key challenge. Inspired by the recent success of foundation models in different domains, robotic learning has been going through a paradigm shift from learning specialist robots on narrow task distributions to learning generalist robots on large-scale multitask...

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Role:
Supervisor


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Funder identifier:
https://ror.org/0439y7842
Funding agency for:
Xiong, Z
Programme:
Centre for Doctoral Training in Autonomous Intelligent Machines and Systems


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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