A survey of autonomous self-reconfiguration methods for robot-based programmable matter

While researchers envision exciting applications for metamorphic systems like programmable matter, current solutions to the shape formation problem are still a long way from meeting their requirements. To dive deeper into this issue, we propose an extensive survey of the current state of the art of self/reconfiguration algorithms and underlying models in modular robotic and self-organizing particle systems. We identify three approaches for solving this problem and we compare the different solutions using a synoptic graphical representation. We then close this survey by confronting existing methods to our vision of programmable matter, and by discussing a number of future research directions that would bring us closer to making it a reality. (C) 2019 Elsevier B.V. All rights reserved.