Ant-like task allocation and recruitment in cooperative robots

Abstract

One of the greatest challenges in robotics is to create machines that are able to interact with unpredictable environments in real time. A possible solution may be to use swarms of robots behaving in a self-organized manner, similar to workers in an ant colony. Efficient mechanisms of division of labour, in particular series-parallel operation and transfer of information among group members, are key components of the tremendous ecological success of ants. Here we show that the general principles regulating division of labour in ant colonies indeed allow the design of flexible, robust and effective robotic systems. Groups of robots using ant-inspired algorithms of decentralized control techniques foraged more efficiently and maintained higher levels of group energy than single robots. But the benefits of group living decreased in larger groups, most probably because of interference during foraging. Intriguingly, a similar relationship between group size and efficiency has been documented in social insects. Moreover, when food items were clustered, groups where robots could recruit other robots in an ant-like manner were more efficient than groups without information transfer, suggesting that group dynamics of swarms of robots may follow rules similar to those governing social insects.

Neural Networks as Mechanisms to Regulate Division of Labor

“…This might not always be the case in nature, as the presence of idle workers may be beneficial for the colony, for example, because of energy constraints (Gordon 1989;Robinson 1992;Krieger et al 2000) or to serve as reserve force that can be mobilized when needed (Wilson 1983;Gordon 1989;Robinson 1992). It would be possible to include such effects in more complex foraging scenarios and to study, for example, the expected relationship between the proportion of idle workers and colony size (Jeanson et al 2007;Dornhaus et al 2009).…”

Measuring Variables Effect to Statistically Model the Multi-Robot Patrolling Problem by Means of ANOVA

“…For example, the relationships between group size and efficiency in robotic ant-like foraging tasks are studied in [15]. Different teams of robots were compared in 3 sets of experiments with different food distributions.…”

Stigmergic MASA: A Stigmergy Based Algorithm for Multi-Target Search

“…To deal with these limits, some effective ways to coordinate multiple agents in their searching task need to take place. Recently many researchers have investigated bio-inspired coordination methods [12] [13], in which agents coordinate on the basis of indirect communication principle known as stigmergy.…”