Robot Learning with Crash Constraints

Alonso Marco
Alonso Marco
Dominik Baumann
Dominik Baumann

IEEE Robotics Autom. Lett., pp. 1439-1446, 2021.

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Abstract:

In the past decade, numerous machine learning algorithms have been shown to successfully learn optimal policies to control real robotic systems. However, it is common to encounter failing behaviors as the learning loop progresses. Specifically, in robot applications where failing is undesired but not catastrophic, many algorithms struggle...More

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