Kinematic synthesis using reinforcement learning

Kaz Vermeer, Reinier Kuppens*, Just Herder

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
17 Downloads (Pure)

Abstract

The presented research demonstrates the synthesis of two-dimensional kinematic mechanisms using feature-based reinforcement learning. As a running example the classic challenge of designing a straight-line mechanism is adopted: a mechanism capable of tracing a straight line as part of its trajectory. This paper presents a basic framework, consisting of elements such as mechanism representations, kinematic simulations and learning algorithms, as well as some of the resulting mechanisms and a comparison to prior art. Series of successful mechanisms have been synthesized for path generation of a straight line and figure-eight.

Original languageEnglish
Title of host publicationASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
Subtitle of host publicationVolume 2A: 44th Design Automation Conference
Place of PublicationNew York, NY, USA
PublisherASME
Number of pages12
ISBN (Print)978-0-7918-5175-3
DOIs
Publication statusPublished - 2018
Event44th Design Automation Conference: ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Quebec City, Canada
Duration: 26 Aug 201829 Aug 2018

Conference

Conference44th Design Automation Conference
Country/TerritoryCanada
CityQuebec City
Period26/08/1829/08/18

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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