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An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap

  • Mostafa Wahby
  • , Daniel Nicolas Hofstadler
  • , Mary Katherine Heinrich
  • , Payam Zahadat
  • , Heiko Hamann

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

The self-organizing bio-hybrid collaboration ofrobots and natural plants allows for a variety of interestingapplications. As an example we investigate how robots can beused to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionaryrobotics approach where task performance is determined bymonitoring the plant's reaction. First, we do initial plantexperiments with simple, predetermined controllers. Then weuse image sampling data as a model of the dynamics ofthe plant tip xy position. Second, we use this approach toevolve robot controllers in simulation. The task is to makethe plant approach three predetermined, distinct points in anxy-plane. Finally, we test the evolved controllers in real plantexperiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tipto many points on the plant, for a model of the plant stemdynamics. Future work will extend to two-axes image samplingfor a 3-d approach.
Original languageEnglish
Title of host publication2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems
Number of pages10
PublisherIEEE
Publication date2016
Pages21-30
ISBN (Electronic)978-1-5090-3534-2
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventInternational Conference on Self-Adaptive and Self-Organizing Systems - Augsburg, Germany
Duration: 12 Sept 201616 Sept 2016
Conference number: 10

Conference

ConferenceInternational Conference on Self-Adaptive and Self-Organizing Systems
Number10
Country/TerritoryGermany
CityAugsburg
Period12/09/201616/09/2016

Keywords

  • biohybrid robotics
  • plant-robot interaction
  • evolutionary robotics
  • image-based plant dynamics modeling
  • sim-to-real transfer

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