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Complex Morphology Neural Network Simulation in Evolutionary Robotics

Published online by Cambridge University Press:  22 July 2019

Grant W. Woodford Open the ORCID record for Grant W. Woodford [Opens in a new window]  and
Mathys C. du Plessis
Grant W. Woodford*
Affiliation:
Department of Computing Sciences, Nelson Mandela University South Campus, Port Elizabeth, South Africa E-mail: mc.duplessis@mandela.ac.za
Mathys C. du Plessis
Affiliation:
Department of Computing Sciences, Nelson Mandela University South Campus, Port Elizabeth, South Africa E-mail: mc.duplessis@mandela.ac.za
*
*Corresponding author. E-mail: s205014224@mandela.ac.za
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Summary

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This paper investigates artificial neural network (ANN)-based simulators as an alternative to physics-based approaches for evolving controllers in simulation for a complex snake-like robot. Prior research has been limited to robots or controllers that are relatively simple. Benchmarks are performed in order to identify effective simulator topologies. Additionally, various controller evolution strategies are proposed, investigated and compared. Using ANN-based simulators for controller fitness estimation during controller evolution is demonstrated to be a viable approach for the high-dimensional problem specified in this work.

Keywords

AutomationControl of robotic systemsMotion planningRobot dynamicsSerial manipulator design and kinematics

Information

Type
Articles
Information
Robotica , Volume 38 , Issue 5 , May 2020 , pp. 886 - 902
Copyright
Copyright © Cambridge University Press 2019

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