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


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.