Generating Artificial Plant Morphologies for Function and Aesthetics through Evolving L-Systems

Abstract

Due to the replacement of natural flora and fauna with urban environments, a significant part of the earth's organisms that function as primary producers have been dispelled. To compensate for the reduction in the amount of primary producers, robotic systems that mimic plant-like organisms are interesting to mimic for their potential functional and aesthetic value in urban environments. To investigate how to utilize plant developmental strategies in order to engender urban artificial plants, we built a simple evolutionary model that applies an L-System based grammar as an abstraction of plant development. In the presented experiments, phytomorphologies (plant morphologies) are iteratively constructed using a context sensitive L-System. The genomic representation of the L-System is subject to mutation by an evolutionary algorithm. These mutations thus alter the developmental rules of these phytomorphologies. We compare the differences between the light absorption of evolving virtual plants that remain static during their life and virtual plants that possess the possibility to move joints that link the separate parts of the virtual plants. Our results show that our evolutionary algorithm did not exploit potential beneficial joint actuation, instead, mostly static structures evolved. The results of our evolving L-System show that it is able to create various phytomorphologies, albeit that the results are preliminary and will be more thoroughly investigated in the future.

Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants

“…When material properties were not suitable to the task, evolution produced less capable robots, characterized by more complex growth controllers, due to their inability to outsource part of the control to their morphology. This result also indicates that taking into account softness and complex body dynamics is extremely important when evolving artificial plants, as opposed to approaches based on more static, rigid kinematic chains (Veenstra et al, 2016).…”

“…VoxCAD allows the quantitatively accurate simulation (Hiller and Lipson, 2012) of the static and dynamic behavior of free-form 3D multi-material structures, which can be characterized by large deformations and heterogeneous properties (e.g., density, stiffness): these features make it particularly suitable for simulating plant-like morphologies, which are instead usually approximated by rigid segments interconnected by joints (Veenstra et al, 2016). The simulator, based on a mass-spring lattice of voxels, was considerably extended with custom features to support our experiments, and coupled with a high-level Python library, 1 were a state of the art evolutionary algorithm (Sect.…”

“…3.1) and plant-like creatures (Sect. 3.2), the system exhibits a number of peculiar features (highlighted throughout the paper) which make it particularly promising for application in this latter domain, distinguishing it from alternative approaches (Von Mammen and Jacob, 2009;Zamuda and Brest, 2014;Veenstra et al, 2015Veenstra et al, , 2016Wahby et al, 2015Wahby et al, , 2016. Particular focus will be on our attempt to integrate biologically plausible developmental dynamics into the system (Sect.…”

Toward Energy Autonomy in Heterogeneous Modular Plant-Inspired Robots through Artificial Evolution

“…However, when only one solar panel is being used, the robot evolved more movement and movement has a clear evolutionary advantage when it tilts the solar module toward the light. Similar to Veenstra et al (2016), evolution does not necessarily pick up movement of solar panels even when there is no cost for movement attributed to it. A significant difference could, however, be seen when a large cost was implemented for movement in the modular robots.…”

“…With an open-loop control system, we can find simple control mechanisms that allow for the optimal energy absorption. While artificial plant systems have been implemented in cellular automata (Hogeweg, 1988;Balzter et al, 1998) as well as virtual creatures (Zamuda and Brest, 2014;Corucci et al, 2016;Veenstra et al, 2016;Zahadat et al, 2016), they have rarely been investigated in a three-dimensional embodied approach other than light-tracking solar panels (Prinsloo and Dobson, 2015). Many evolutionary robotics experiments have focused on acquiring behavior typical of consumers (Sims, 1994a,b;Pfeifer and Bongard, 2006;Vargas et al, 2014), we instead look at how primary energy producers can evolve in artificial systems.…”