Programmable Self-Disassembly for Shape Formation in Large-Scale Robotic Collectives

Melvin Gauci, Radhika Nagpal, Michael Rubenstein

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We present a method for a large-scale robot collective to autonomously form a wide range of user-specified shapes. In contrast to most existing work, our method uses a subtractive approach rather than an additive one, and is the first such method to be demonstrated on robots that operate in continuous space. An initial dense, stationary configuration of robots distributively forms a coordinate system, and each robot decides if it is part of the desired shape. Non-shape robots then remove themselves from the configuration using a single external light source as a motion guide. The subtractive approach allows for a higher degree of motion parallelism than additive approaches; it is also tolerant of much lower-precision motion. Experiments with 725 Kilobot robots allow us to compare our method against an additive one that was previously evaluated on the same platform. The subtractive method leads to higher reliability and an order-of-magnitude improvement in shape formation speed.
Original languageEnglish (US)
Title of host publicationDistributed Autonomous Robotic Systems
Subtitle of host publicationThe 13th International Symposium
EditorsRoderich Gross, Andreas Kolling, Spring Berman, Emilio Frazzoli, Alcherio Martinoli, Fumitoshi Matsuno, Melvin Gauci
PublisherSpringer International Publishing
Number of pages14
ISBN (Print)978-3319730066
StatePublished - 2016

Publication series

NameSpringer Proceedings in Advanced Robotics
ISSN (Print)2511-1256

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