The Statistical Dynamics of Programmed Self-assembly

Abstract— We describe how a graph grammar program for robotic self-assembly, together with measurements of kinetic rate data yield a Markov Process model of the dynamics of programmed self-assembly. We demonstrate and evalidate the method by applying it to a physical testbed consisting of a number of “programmable parts”, which are able to control their local interactions according to their on-board programs. We describe a technique for obtaining kinetic rate constants from simulation and a comparison of the behavior predicted by the Markov model with the behavior predicted by a low-level simulation of the system.

• Type: Conference
• Year: 2006
• Where: ICRA
• Authors: Nils Napp, Samuel Burden, Eric Klavins
• Keywords: ICRA 2006, Kinetic Rate, Kinetic Rate Data, Markov Process Model, Robotics