Robot End Effector Tracking Using Predictive Multisensory Integration
We propose a biologically inspired model that enables a humanoid robot to learn how to track its end effector by integrating visual and proprioceptive cues as it interacts with the environment. A key novel feature of this model is the incorporation of sensorimotor prediction, where the robot predict...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2018-10-01
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Series: | Frontiers in Neurorobotics |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fnbot.2018.00066/full |