It is often postulated that robots will eventually face conditions, whether on extraterrestrial bodies or deep underwater, that could not have been predicted by their designers. In such conditions, truly autonomous robots should be able to describe and talk about their environments in order to collectively find appropriate solutions. We designed an emergent naming systems for such purposes. This paper focuses on a shortest-path discovery scenario in an unstructured environment, where landmarks are collectively named, by a swarm of robots, as they are discovered. The robots use those landmarks as beacons for navigation and score them according to their relevance to the task at hand. Meanwhile the naming system enables the swarm to update these scores asynchronously, using very little bandwidth. We compare our naming-based navigation performances with swarms that do not communicate and swarms with prior knowledge of the environment, and find that our approach performs similarly to the latter. This has significant implications on the link between space conceptualisation and language, as this proto-language enables the robots to find a topological path without individually mapping the environment.

Self-organised aggregation, the formation of large clusters of independent agents, is an important process in swarm robotics systems since it is the prerequisite for more complex collective behaviours. Previous work on self-organised aggregation focused on the study of the individual mechanisms required to allow a swarm to form a single aggregate. In this paper, we discuss an analytical model which looks at the possibility to use the concept of informed individuals to allow the swarm to distribute on different aggregation sites according to proportions of individuals at each site arbitrarily chosen by the designer. Informed individuals are opinionated agents that selectively prefer an aggregation site and avoid to rest on the non-preferred sites. We study environments with two aggregation sites, and consider two different scenarios: one in which the informed individuals are equally distributed in numbers between the two sites; and one in which informed individuals for one type of site are three times more numerous than those on the other site. Our objective is to find out whether and for what range of model parameters the swarm distributes between the two sites according to the relative distribution of informed agents among the two sites. The analysis of the model shows that the designer capability to exploit informed individuals to control how the swarm aggregates depends on the environmental conditions. For intermediate values of the site carrying capacity, a small minority of informed individuals is able to guide the dynamics as desired by the designer. We also show that the larger the site carrying capacity the larger the total proportion of informed individuals required to lead the swarm to the desired distribution of individuals between the two sites.