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Erschienen in:
A Comparative Study of Large-Scale Variants of CMA-ES Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Directed Locomotion for Modular Robots with Evolvable Morphologies

verfasst von : Gongjin Lan, Milan Jelisavcic, Diederik M. Roijers, Evert Haasdijk, A. E. Eiben

Erschienen in: Parallel Problem Solving from Nature – PPSN XV

Verlag: Springer International Publishing

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Abstract

Morphologically evolving robot systems need to include a learning period right after ‘birth’ to acquire a controller that fits the newly created body. In this paper, we investigate learning one skill in particular: walking in a given direction. To this end, we apply the HyperNEAT algorithm guided by a fitness function that balances the distance travelled in a direction and the deviation between the desired and the actually travelled directions. We validate this method on a variety of modular robots with different shapes and sizes and observe that the best controllers produce trajectories that accurately follow the correct direction and reach a considerable distance in the given test interval.

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Vorheriges Kapitel Critical Fractile Optimization Method Using Truncated Halton Sequence with Application to SAW Filter Design
Nächstes Kapitel Optimisation and Illumination of a Real-World Workforce Scheduling and Routing Application (WSRP) via Map-Elites
Fußnoten
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Metadaten
Titel
Directed Locomotion for Modular Robots with Evolvable Morphologies
verfasst von
Gongjin Lan
Milan Jelisavcic
Diederik M. Roijers
Evert Haasdijk
A. E. Eiben
Copyright-Jahr
2018
Buch
Parallel Problem Solving from Nature – PPSN XV

Print ISBN: 978-3-319-99252-5

Electronic ISBN: 978-3-319-99253-2

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-99253-2_38

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