Accession Number : AD1003111


Title :   Human-Swarm Interactions Based on Managing Attractors


Descriptive Note : Conference Paper


Corporate Author : Air Force Research Laboratory/RISC Rome


Personal Author(s) : Brown,Daniel S ; Kerman,Sean C ; Goodrich,Michael A


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1003111.pdf


Report Date : 06 Mar 2014


Pagination or Media Count : 9


Abstract : Leveraging the abilities of multiple affordable robots as a swarm is enticing because of the resulting robustness and emergent behaviors of a swarm. However, because swarms are composed of many different agents, it is difficult for a human to influence the swarm by managing individual agents. Instead, we propose that human influence should focus on (a) managing the higher level attractors of the swarm system and (b) managing trade-offs that appear in mission relevant performance. We claim that managing attractors theoretically allows a human to abstract the details of individual agents and focus on managing the collective as a whole. Using a swarm model with two attractors, we demonstrate this concept by showing how limited human influence can cause the swarm to switch between attractors. We further claim that using quorum sensing allows a human to manage trade-offs between the scalability of interactions and mitigating the vulnerability of the swarm to agent failures.


Descriptors :   ROBOTS


Distribution Statement : APPROVED FOR PUBLIC RELEASE