  One of the main tasks for autonomous robot swarms is to collectively decide
on the best available option. Achieving that requires a high quality
communication between the agents that may not be always available in a real
world environment. In this paper we introduce the communication-constrained
collective decision-making problem where some areas of the environment limit
the agents' ability to communicate, either by reducing success rate or blocking
the communication channels. We propose a decentralised algorithm for mapping
environmental features for robot swarms as well as improving collective
decision making in communication-limited environments without prior knowledge
of the communication landscape. Our results show that making a collective aware
of the communication environment can improve the speed of convergence in the
presence of communication limitations, at least 3 times faster, without
sacrificing accuracy.
