Learning Coupled Forward-Inverse Models with Combined Prediction Errors (ICRA 2018)

Koert, D.;Maeda, G.; Neumann, G.; Peters, J. Learning Coupled Forward-Inverse Models with Combined Prediction Errors [BibTeX][pdf]

This work revisits concepts from sensorimotor learning algorithms based on mixture-of-experts, and MOSAIC in particular. It proposes a novel formulation to learn one-to-many mappings, such as the ones found in the Inverse Kinematics of redundant arms.  It reports experiments using a real KUKA lightweight arm where different IK solutions are found as a function of the context. The figure below is part of the paper and gives the overall motivation.

doro_icra2018

 

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