Sponsor
This work was supported by the Cross-Disciplinary Semiconductor Research (CSR) Program award G15173 from the Semiconductor Research Corporation (SRC).
Published In
Frontiers in Robotics and AI
Document Type
Article
Publication Date
2-2016
Subjects
Electronic data processing -- Distributed processing
Abstract
This paper discusses a novel approach to managing complexity in a large self-assembled system, by utilizing the self-assembling components themselves to address the complexity. A particular challenge is discussed – namely the question of how to deal with elements that are assembled in different orientations from each other – and a solution based on the idea ofintrospective circuitry is described. A methodology for using a set of cells to determine a nearby cell’s orientation is given, leading to a slow (O(n)) means of orienting a 2D region of cells. A modified algorithm is then describe to allow parallel analysis of/adaption to dis-oriented cells, thus allowing re-orientation of an entire 2D region of cells with better-than-linear time performance (O(sqrt(n))). The significance of this work is discussed not only in terms of managing arrays of dis-oriented cells but also more importantly as an example of the usefulness of local, distributed self-configuration to create and use introspective circuitry.
DOI
10.3389/frobt.2016.00002
Persistent Identifier
http://archives.pdx.edu/ds/psu/17953
Citation Details
Macias, N., Teuscher, C., and Durbeck (2016). Design of Introspective Circuits for Analysis of Cell-Level Dis-orientation in Self-Assembled Cellular Systems. Frontiers in Robotics and AI. 3 (2); 1-13.
Description
Copyright © 2016 Macias, Teuscher and Durbeck. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Originally published in Frontiers in Robotics and AI and can be found online at: http://dx.doi.org/10.3389/frobt.2016.00002