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. 2019 Oct 4;6(5):579–594. doi: 10.1089/soro.2018.0126

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© Matthew Ishige et al. 2019; Published by Mary Ann Liebert, Inc.

This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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FIG. 1. — Overview of SenseCPG-PGPE. Displacement distance or angle of each actuator in a control objective (depicted here as a caterpillar-like robot) obeys the phase of an active rotator in the CPG-based controller. The feedback controller receives the mechanosensor values obtained across the body and calculates feedback to the CPG-based controller according to the equation. After running this cycle for several steps, the PGPE algorithm updates the parameters in the feedback controller based on performance. CPG, central pattern generator; PGPE, policy gradients with parameter-based exploration.