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Evolved Control of Natural Plants: Crossing the Reality Gap for User-Defined Steering of Growth and Motion DANIEL NICOLAS HOFSTADLER, University of Graz MOSTAFA WAHBY, Paderborn University and University of L beck MARY KATHERINE HEINRICH, Centre for IT and Architecture HEIKO HAMANN, Paderborn University and University of L beck PAYAM ZAHADAT, University of Graz PHIL AYRES, Centre for IT and Architecture THOMAS SCHMICKL, University of Graz Mixing societies of natural and artificial systems can provide interesting and potentially fruitful research targets. Here we mix robotic setups and natural plants in order to steer the motion behavior of plants while growing. The robotic setup uses a camera to observe the plant and uses a pair of light sources to trigger phototropic response, steering the plant to user-defined targets. An evolutionary robotic approach is used to design a controller for the setup. Initially, preliminary experiments are performed with a simple predetermined controller and a growing bean plant. The plant behavior in response to the simple controller is captured by image processing, and a model of the plant tip dynamics is developed. The model is used in simulation to evolve a robot controller that steers the plant tip such that it follows
ACM Transactions on Autonomous and Adaptive Systems (TAAS) – Association for Computing Machinery
Published: Oct 9, 2017
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