Title :
Gaussian reconstruction of swarm behavior from partial data
Author :
Wagner, Glenn ; Choset, Howie
Author_Institution :
Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Swarms consist of large numbers of individual agents that generally maintain no fixed relative positions, which makes describing the behavior of the swarm as a whole difficult. Furthermore, the high number of agents leads to frequent occlusions that prevent observations of the entire swarm. In this paper, we represent the behavior of swarms using velocity fields, yielding a description which is invariant to the number of agents in a swarm, and the position, orientation, and scale of the swarm. The velocity field representation allows the behavior of swarms to be modeled as a Gaussian distribution. We demonstrate that this Gaussian model can be used to reconstruct the behavior of the swarm as a whole from partial observations.
Keywords :
Gaussian distribution; data analysis; multi-agent systems; pattern classification; Gaussian distribution; Gaussian model; Gaussian reconstruction; agent orientation; agent position; agent swarm; behavior classification; occlusion; partial data; partial observation; swarm behavior; velocity field representation; Biological system modeling; Computational modeling; Data models; Gaussian distribution; Manifolds; Shape; Transforms;
Conference_Titel :
Robotics and Automation (ICRA), 2015 IEEE International Conference on
Conference_Location :
Seattle, WA
DOI :
10.1109/ICRA.2015.7140020