Modeling dynamic swarms

Modeling dynamic swarms

This paper proposes the problem of modeling video sequences of dynamic swarms (DS). We define DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds ...

Swarms in Dynamic Environments

Charged particle swarm optimization (CPSO) is well suited to the dynamic search problem since inter-particle repulsion maintains population diversity and good tracking can be achieved with a simple algorithm. This work extends the application of CPSO to the dynamic problem by considering a bi-modal parabolic environment of high spatial and temporal severity. Two types of charged swarms and an a...

Dynamic Search With Charged Swarms

Two novel particle swarm optimization (PSO) algorithms are used to track and optimize a 3dimensional parabolic benchmark function where the optimum location changes randomly and with high severity. The new algorithms are based on an analogy of electrostatic energy with charged particles. For comparison, the same experiment is performed with a conventional PSO algorithm. It is found that the bes...

Particle Swarms for Dynamic Optimization Problems

Dynamic Task Assignment in Robot Swarms

A large group of robots will often be partitioned into subgroups, each subgroup performing a different task. This paper presents four distributed algorithms for assigning swarms of homogenous robots to subgroups to meet a specified global task distribution. Algorithm Random-Choice selects tasks randomly, but runs in constant time. Algorithm Extreme-Comm compiles a complete inventory of all the ...