Sep 26, 2019 · We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned reward ...
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Our framework for data-driven robotics results in policies which are: Faster than human in tasks involving complex interaction among several objects. Robust ...
We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned ...
Sep 26, 2019 · It is shown that using the framework presented, it is possible to train agents to perform a variety of challenging manipulation tasks ...
Duration: 3:01
Posted: Sep 27, 2019
Posted: Sep 27, 2019
This work proposes a framework that enables continuous data collection through demonstrations, reward sketching and experience evaluation.
The more tasks the robot solves, the more data it gathers, and all of it becomes useful when learning new skills. Our framework for data-driven robotics results ...
Nov 18, 2022 · This study proposes a three-step machine-learning framework for extracting the dynamic equations of serial manipulators from data.
Several recent large-scale robotic datasets were released recently to advance the data-driven robotics. ... Acme: A research framework for distributed ...
The DataDriver library is an extension for Robot Framework®. DataDriver creates new test cases based on a Data-File that contains the data for Data-Driven ...