A generalized framework for procedural generation of three-dimensional static and dynamic plant model geometries

This work presents a new framework for procedural generation of dynamic 3D plant model geometries, which has been implemented in the Helios modeling system. Key goals of this work were to develop a model that 1) has a generalized set of parameters that are conserved across species, which are botanically-consistent and readily measurable; 2) significantly reduces the time and effort needed to create photorealistic, dynamically evolving plant models; 3) allows for encoding of the entire plant structure into a character-based representation that can integrated with machine learning models, and 4) includes realistic and computationally efficient collision physics. A model framework that satisfies these specifications is presented in this report. The model was implemented in the Helios C++ and PyHelios Python frameworks, which are open-source libraries that can be used to generate 3D plant geometries based on this model.