Name
Abstract | ||
|---|---|---|
One of basic problems of multi-target search in swarm robotics is how to allocate the tasks of searching targets among robots. In this paper, the formal description of the problem of multi-target search and task allocation are presented. Inspired by division labour of wasp swarm, the strategy of task allocation of multi-target search based on the response threshold model in swarm robotics is prompted. The states of robots are divided into wander, search and marking target. Robots adopt random search in global search phase and particle swarm algorithm in local search in order to illustrate the effectiveness of the strategy. Simulation results show the method is effective and feasible. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1504/IJWMC.2014.062039 | International Journal of Wireless and Mobile Computing |
Keywords | Field | DocType |
swarm robotics,particle swarm | Particle swarm optimization,Swarm behaviour,Computer science,Ant robotics,Swarm intelligence,Multi-swarm optimization,Artificial intelligence,Local search (optimization),Machine learning,Metaheuristic,Swarm robotics | Journal |
Volume | Issue | Citations |
7 | 3 | 4 |
PageRank | References | Authors |
0.50 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoyou Zhang | 1 | 7 | 1.67 |
| Jianchao Zeng | 2 | 930 | 94.89 |
| Songdong Xue | 3 | 24 | 4.31 |