Evolution of Transferable and Self-Organized Communication Modules for Solving Multiple Swarm Robotics Tasks

A key aspect of decentralized multirobot coordination is communication. However, beyond simple signaling, there are only few reports in the literature on the successful evolution of communication, with successes largely dependent on specific tasks and evolutionary setups. Thus, there is a lack of standardized communication frameworks that can be applied to different tasks without the need to redesign, rebuild, or re-evolve the entire system for every new task. In this article, we propose a novel communication module that does not need to be modified for its use in different tasks. Each robot has a coordinate (state) in a virtual communication space. The communication space is partitioned into virtual regions, and each region is linked to a physical behavior, such as seeking resources, phototaxis, or recharging the battery. A robot’s individual behavior is determined by the region to which its current communication state belongs. Since robots can navigate the communication space and continually broadcast their coordinates to neighbors within range, robot swarms can effectively coordinate their behavior in a self-organized manner. We demonstrate that the same evolved communication module is effective in three swarm robotics tasks: 1) the physical aggregation of the robots into groups of a desired size; 2) the formation of desired swarm geometries; and 3) a foraging task based on temporal role allocation. The results show that the communication module provides good and scalable performance in all tasks, representing a significant step toward a task-agnostic communication framework for robot swarms.