Learning Inverse Statics Models Efficiently With Symmetry-Based Exploration

Learning Inverse Statics Models Efficiently With Symmetry-Based Exploration

Learning (inverse) kinematics and dynamics models of dexterous robots for the entire action or observation space is challenging and costly. Sampling the entire space is usually intractable in terms of time, tear, and wear. We propose an efficient approach to learn inverse statics models—primarily fo...

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Bibliographic Details
Main Authors: Rania Rayyes, Daniel Kubus, Jochen Steil
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-10-01
Series:Frontiers in Neurorobotics
Subjects:
symmetries
inverse statics models
inverse dynamics models
efficient learning
direction sampling
goal babbling
Online Access:https://www.frontiersin.org/article/10.3389/fnbot.2018.00068/full

Internet

https://www.frontiersin.org/article/10.3389/fnbot.2018.00068/full

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