Related papers: Visionary: Vision architecture discovery for robot learning

Visionary: Vision architecture discovery for robot learning

URL: http://arxiv.org/abs/2103.14633v1
Date: Fri, 26 Mar 2021 17:51:43 GMT
Title: Visionary: Vision architecture discovery for robot learning
Authors: Iretiayo Akinola, Anelia Angelova, Yao Lu, Yevgen Chebotar, Dmitry Kalashnikov, Jacob Varley, Julian Ibarz, Michael S. Ryoo
Abstract summary: We propose a vision-based architecture search algorithm for robot manipulation learning, which discovers interactions between low dimension action inputs and high dimensional visual inputs. Our approach automatically designs architectures while training on the task - discovering novel ways of combining and attending image feature representations with actions as well as features from previous layers.
Score: 58.67846907923373
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: We propose a vision-based architecture search algorithm for robot manipulation learning, which discovers interactions between low dimension action inputs and high dimensional visual inputs. Our approach automatically designs architectures while training on the task - discovering novel ways of combining and attending image feature representations with actions as well as features from previous layers. The obtained new architectures demonstrate better task success rates, in some cases with a large margin, compared to a recent high performing baseline. Our real robot experiments also confirm that it improves grasping performance by 6%. This is the first approach to demonstrate a successful neural architecture search and attention connectivity search for a real-robot task.

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