individual
What campus are you from?
Daytona Beach
Authors' Class Standing
Nathan George, Senior
Lead Presenter's Name
Nathan George
Faculty Mentor Name
Bryan Watson
Abstract
Swarms of simple, identical robots can be resilient against members failing by operating without a central node or point of failure. These types of swarms are called decentralized because there is no central agent or robot controlling the rest. While many decentralized swarm algorithms focus on coordination or environmental signaling, this research focuses on arranging the swarm members into a scale-free network topology from a random starting distribution without central control or planning. This topology enables efficient passing of complex, targeted messages between agents in the swarm. We propose using a biologically inspired quorum sensing algorithm to enable the swarm to self-organize. The algorithm is inspired by the behavior of fungal and bacterial biofilms and will be tested using a multi-agent simulation. The success of the algorithm is determined by the condition 2< λ< 3, where k^(-λ) is the power law distribution of a scale-free network. This condition indicates the emergence of a typical scale-free network, demonstrating that biologically inspired quorum sensing can enable self-organization into scale-free networks. Achieving scale-free structures in decentralized swarms enables targeted communication between agents in a swarm of any size, from computers passing messages on a home network, to robots comparing live sensor readings.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Development of a Bio-Inspired Quorum Sensing Algorithm for Self-Organizing Scale-Free Networks
Swarms of simple, identical robots can be resilient against members failing by operating without a central node or point of failure. These types of swarms are called decentralized because there is no central agent or robot controlling the rest. While many decentralized swarm algorithms focus on coordination or environmental signaling, this research focuses on arranging the swarm members into a scale-free network topology from a random starting distribution without central control or planning. This topology enables efficient passing of complex, targeted messages between agents in the swarm. We propose using a biologically inspired quorum sensing algorithm to enable the swarm to self-organize. The algorithm is inspired by the behavior of fungal and bacterial biofilms and will be tested using a multi-agent simulation. The success of the algorithm is determined by the condition 2< λ< 3, where k^(-λ) is the power law distribution of a scale-free network. This condition indicates the emergence of a typical scale-free network, demonstrating that biologically inspired quorum sensing can enable self-organization into scale-free networks. Achieving scale-free structures in decentralized swarms enables targeted communication between agents in a swarm of any size, from computers passing messages on a home network, to robots comparing live sensor readings.