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: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The self-organizing bio-hybrid collaboration of robots and natural plants allows for a variety of interesting applications. As an example we investigate how robots can be used to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionary robotics approach where task performance is determined by monitoring the plant's reaction. First, we do initial plant experiments with simple, predetermined controllers. Then we use image sampling data as a model of the dynamics of the plant tip xy position. Second, we use this approach to evolve robot controllers in simulation. The task is to make the plant approach three predetermined, distinct points in an xy-plane. Finally, we test the evolved controllers in real plant experiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tip to many points on the plant, for a model of the plant stem dynamics. Future work will extend to two-axes image sampling for a 3-d approach.
Original languageEnglish
Title of host publicationSelf-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on
PublisherIEEE
Publication date8 Dec 2016
ISBN (Print)978-1-5090-3535-9
ISBN (Electronic)978-1-5090-3534-2
DOIs
Publication statusPublished - 8 Dec 2016
EventSelf-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on - IEEE, Augsburg, Germany
Duration: 12 Sep 201616 Sep 2016
http://ieeexplore.ieee.org/servlet/opac?punumber=1001843

Conference

ConferenceSelf-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on
LocationIEEE
CountryGermany
CityAugsburg
Period12/09/201616/09/2016
Internet address

Keywords

  • plant modeling
  • Bio-hybrid
  • evolutionary robotics
  • reality gap
  • self-organization

Artistic research

  • No

Cite this

Wahby, M., Hofstadler, D. N., Heinrich, M. K., Zahadat, P., & Hamann, H. (2016). An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap. In Self-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on IEEE. https://doi.org/10.1109/SASO.2016.8
Wahby, Mostafa ; Hofstadler, Daniel Nicolas ; Heinrich, Mary Katherine ; Zahadat, Payam ; Hamann, Heiko. / An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap. Self-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on. IEEE, 2016.
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title = "An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap",
abstract = "The self-organizing bio-hybrid collaboration of robots and natural plants allows for a variety of interesting applications. As an example we investigate how robots can be used to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionary robotics approach where task performance is determined by monitoring the plant's reaction. First, we do initial plant experiments with simple, predetermined controllers. Then we use image sampling data as a model of the dynamics of the plant tip xy position. Second, we use this approach to evolve robot controllers in simulation. The task is to make the plant approach three predetermined, distinct points in an xy-plane. Finally, we test the evolved controllers in real plant experiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tip to many points on the plant, for a model of the plant stem dynamics. Future work will extend to two-axes image sampling for a 3-d approach.",
keywords = "plant modeling, Bio-hybrid, evolutionary robotics, reality gap, self-organization",
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Wahby, M, Hofstadler, DN, Heinrich, MK, Zahadat, P & Hamann, H 2016, An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap. in Self-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on. IEEE, Self-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on, Augsburg, Germany, 12/09/2016. https://doi.org/10.1109/SASO.2016.8

An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap. / Wahby, Mostafa; Hofstadler, Daniel Nicolas; Heinrich, Mary Katherine; Zahadat, Payam; Hamann, Heiko.

Self-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on. IEEE, 2016.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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AU - Hamann, Heiko

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N2 - The self-organizing bio-hybrid collaboration of robots and natural plants allows for a variety of interesting applications. As an example we investigate how robots can be used to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionary robotics approach where task performance is determined by monitoring the plant's reaction. First, we do initial plant experiments with simple, predetermined controllers. Then we use image sampling data as a model of the dynamics of the plant tip xy position. Second, we use this approach to evolve robot controllers in simulation. The task is to make the plant approach three predetermined, distinct points in an xy-plane. Finally, we test the evolved controllers in real plant experiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tip to many points on the plant, for a model of the plant stem dynamics. Future work will extend to two-axes image sampling for a 3-d approach.

AB - The self-organizing bio-hybrid collaboration of robots and natural plants allows for a variety of interesting applications. As an example we investigate how robots can be used to control the growth and motion of a natural plant, using LEDs to provide stimuli. We follow an evolutionary robotics approach where task performance is determined by monitoring the plant's reaction. First, we do initial plant experiments with simple, predetermined controllers. Then we use image sampling data as a model of the dynamics of the plant tip xy position. Second, we use this approach to evolve robot controllers in simulation. The task is to make the plant approach three predetermined, distinct points in an xy-plane. Finally, we test the evolved controllers in real plant experiments and find that we cross the reality gap successfully. We shortly describe how we have extended from plant tip to many points on the plant, for a model of the plant stem dynamics. Future work will extend to two-axes image sampling for a 3-d approach.

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Wahby M, Hofstadler DN, Heinrich MK, Zahadat P, Hamann H. An Evolutionary Robotics Approach to the Control of Plant Growth and Motion: Modeling Plants and Crossing the Reality Gap. In Self-Adaptive and Self-Organizing Systems (SASO), 2016 IEEE 10th International Conference on. IEEE. 2016 https://doi.org/10.1109/SASO.2016.8