A distributed algorithm for 2D shape duplication with smart pebble robots
Name
Rus_A distributed.pdf
Size
225.37 KB
Format
Adobe PDF
Checksum (MD5)
69d636d4dd586e15296df3d79d503691
Author(s)
Gilpin, Kyle W.
Rus, Daniela L.
Date Issued
May 2012
Journal
Proceedings of the 2012 IEEE International Conference on Robotics and Automation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Gilpin, Kyle, and Daniela Rus. “A Distributed Algorithm for 2D Shape Duplication with Smart Pebble Robots.” 2012 IEEE International Conference on Robotics and Automation (May 2012).
Version
Author's final manuscript
Abstract
We present our digital fabrication technique for manufacturing active objects in 2D from a collection of smart particles. Given a passive model of the object to be formed, we envision submerging this original in a vat of smart particles, executing the new shape duplication algorithm described in this paper, and then brushing aside any extra modules to reveal both the original object and an exact copy, side-by-side. Extensions to the duplication algorithm can be used to create a magnified version of the original or multiple copies of the model object. Our novel duplication algorithm uses a distributed approach to identify the geometric specification of the object being duplicated and then forms the duplicate from spare modules in the vicinity of the original. This paper details the duplication algorithm and the features that make it robust to (1) an imperfect packing of the modules around the original object; (2) missing communication links between neighboring modules; and (3) missing modules in the vicinity of the duplicate object(s). We show that the algorithm requires O(1) storage space per module and that the algorithm exchanges O(n) messages per module. Finally, we present experimental results from 60 hardware trials and 150 simulations. These experiments demonstrate the algorithm working correctly and reliably despite broken communication links and missing modules.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. School of Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICRA.2012.6225227
