This objective of this research award is to create a new generalization of cellular self-organization as a way to automate the design and control of complex and interdisciplinary systems. Concepts from nature such as evolution, cellular organization, and self-organizing behavior serve as the inspiration for the research. The researchers are creating a software framework built on four elements: graphs, fields, rules, and rule decisions. The graphs are used to define system architecture and dimensions and exist within a three-dimensional physics-based simulator environment with pertinent internal state variables (positions, velocities, accelerations, temperatures, stresses, etc.). Rules and rule decisions govern how graphs change in response to state variables and external field effects like gravity or temperature in a manner that mimics true physical and biological effects.
The computational framework will enable the ?cyber-physical boundary? to be easily shifted. For example, the framework would serve as a design automation tool to design a device before fabrication (simulating the environment of the device virtually) and also used as a control system for the device in actual operation so that the device might adapt to changes in the environment. This would occur by monitoring real-world fields from external sensors and transforming the graph or configuration of the resulting reconfigurable device. The research is a generalization of various published techniques (e.g. cellular automaton, topology optimization, and claytronics) under a single method. Such a framework is necessary for solving interdisciplinary and multi-physics design problems such as those found in mechatronics and robotics. The results will be widely disseminated for greatest impact.
