Deterministic Leader Election in Programmable Matter
This solves a fundamental coordination problem for programmable matter systems, enabling improved task performance in applications like swarm robotics.
The paper tackles the problem of electing a unique leader in programmable matter systems of connected amoebots, achieving the first deterministic algorithm that works under minimal assumptions of initially contracted amoebots, without randomization or extra conditions like known chirality.
Addressing a fundamental problem in programmable matter, we present the first deterministic algorithm to elect a unique leader in a system of connected amoebots assuming only that amoebots are initially contracted. Previous algorithms either used randomization, made various assumptions (shapes with no holes, or known shared chirality), or elected several co-leaders in some cases. Some of the building blocks we introduce in constructing the algorithm are of interest by themselves, especially the procedure we present for reaching common chirality among the amoebots. Given the leader election and the chirality agreement building block, it is known that various tasks in programmable matter can be performed or improved. The main idea of the new algorithm is the usage of the ability of the amoebots to move, which previous leader election algorithms have not used.