Self-Organization in Biological Systems
Self-Organization in Biological Systems
From swarm intelligence to swarm robotics
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
Swarm robotics: from sources of inspiration to domains of application
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
Efficient multi-foraging in swarm robotics
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Taming the complexity of temporal epistemic reasoning
FroCoS'09 Proceedings of the 7th international conference on Frontiers of combining systems
Formal verification of probabilistic swarm behaviours
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Improving energy efficiency based on behavioral model in a swarm of cooperative foraging robots
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Analysing robot swarm behaviour via probabilistic model checking
Robotics and Autonomous Systems
Foraging swarm robots system adopting honey bee swarm for improving energy efficiency
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Swarm-like Methodologies for Executing Tasks with Deadlines
Journal of Intelligent and Robotic Systems
Towards temporal verification of swarm robotic systems
Robotics and Autonomous Systems
Hi-index | 0.00 |
This paper presents a simple adaptation mechanism to automatically adjust the ratio of foragers to resters (division of labour) in a swarm of foraging robots and hence maximise the net energy income to the swarm. Three adaptation rules are introduced based on local sensing and communications. Individual robots use internal cues (successful food retrieval), environmental cues (collisions with teammates while searching for food) and social cues (teammate success in food retrieval) to dynamically vary the time spent foraging or resting. The paper investigates the effectiveness of a number of strategies based upon different combinations of cues, and demonstrates successful adaptive emergent division of labour. Strategies which employ the social cues are shown to lead to the fastest adaptation to changes in food density and we see that social cues have most impact when food density is low: robots need to cooperate more when energy is scarce.