Programmable Self-disassembly for Shape Formation in Large-Scale Robot Collectives

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.

[1]  Daniela Rus,et al.  Robot pebbles: One centimeter modules for programmable matter through self-disassembly , 2010, 2010 IEEE International Conference on Robotics and Automation.

[2]  Gregory S. Chirikjian,et al.  Modular Self-Reconfigurable Robot Systems , 2007 .

[3]  Hod Lipson,et al.  Robotics: Self-reproducing machines , 2005, Nature.

[4]  Guy Theraulaz,et al.  Self-Organization in Biological Systems: (Traduction Japonaise par Matsumoto, T., & Nabuhiro, S.) , 2009 .

[5]  Hod Lipson,et al.  Three Dimensional Stochastic Reconfiguration of Modular Robots , 2005, Robotics: Science and Systems.

[6]  Iuliu Vasilescu,et al.  Miche: Modular Shape Formation by Self-Disassembly , 2008, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[7]  Guy Theraulaz,et al.  Self-Organization in Biological Systems , 2001, Princeton studies in complexity.

[8]  Anders Lyhne Christensen,et al.  SWARMORPH: Multirobot Morphogenesis Using Directional Self-Assembly , 2009, IEEE Transactions on Robotics.

[9]  Radhika Nagpal,et al.  Self-Reconfiguration Using Directed Growth , 2004, DARS.

[10]  David C. Moore,et al.  Robust distributed network localization with noisy range measurements , 2004, SenSys '04.

[11]  Marco Dorigo,et al.  Autonomous Self-Assembly in Swarm-Bots , 2006, IEEE Transactions on Robotics.

[12]  Eric Klavins,et al.  Programmable parts: a demonstration of the grammatical approach to self-organization , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Alcherio Martinoli,et al.  Synthesizing Rulesets for Programmable Robotic Self-assembly: A Case Study Using Floating Miniaturized Robots , 2016, ANTS Conference.

[14]  Seth Copen Goldstein,et al.  Scalable shape sculpting via hole motion: motion planning in lattice-constrained modular robots , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[15]  J. Deneubourg,et al.  Self-assemblages in insect societies , 2002, Insectes Sociaux.

[16]  Radhika Nagpal,et al.  Programmable self-assembly in a thousand-robot swarm , 2014, Science.