Evolution of Signaling in a Multi-Robot System: Categorization and Communication
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
ROBOTRAK: a centralized real-time monitoring, control, and coordination system for robot swarms
Proceedings of the 1st international conference on Robot communication and coordination
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Connection Science
Fitness functions in evolutionary robotics: A survey and analysis
Robotics and Autonomous Systems
Strengths and synergies of evolved and designed controllers: A study within collective robotics
Artificial Intelligence
From fireflies to fault-tolerant swarms of robots
IEEE Transactions on Evolutionary Computation
Evolution of signalling in a group of robots controlled by dynamic neural networks
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
Evolution of acoustic communication between two cooperating robots
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
"Look out!": socially-mediated obstacle avoidance in collective transport
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Evolutionary synthesis of collective behavior
CollSec'10 Proceedings of the 2010 international conference on Collaborative methods for security and privacy
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In social insects, both self-organisation and communication play a crucial role for the accomplishment of many tasks at a collective level. Communication is performed with different modalities, which can be roughly classified into three classes: indirect (stigmergic) communication, direct interactions and direct communication. The use of stigmergic communication is predominant in social insects (e.g. the pheromone trails in ants), where, however, direct interactions (e.g. antennation in ants) and direct communication (e.g. the waggle dance in honey bees) can also be observed. Taking inspiration from insect societies, we present an experimental study of self-organising behaviours for a group of robots, which exploit communication to coordinate their activities. In particular, the robots are placed in an arena presenting holes and open borders, which they should avoid while moving coordinately. Artificial evolution is responsible for the synthesis in a simulated environment of the robot’s neural controllers, which are subsequently tested on physical robots. We study different communication strategies among the robots: no direct communication, handcrafted signalling and a completely evolved approach. We show that the latter is the most efficient, suggesting that artificial evolution can produce behaviours that are more adaptive than those obtained with conventional design methodologies. Moreover, we show that the evolved controllers produce a self-organising system that is robust enough to be tested on physical robots, notwithstanding the huge gap between simulation and reality.