Multi-Robot Fish Path Planning Based on the Modified A* Algorithm
Qiang Hong, Mei Xiao Chen, Yan Deng
- Year
- 2014
- Citations
- 2
Abstract
Based on improved A* algorithm, this paper proposes the optimal path planning of robot fish in globally known environment, so as to achieve better coordination between the robot fish by means of improving their path planning. In the known obstacle environment which is rasterized, target nodes are generated via smoothing A* algorithm. The unnecessary connection points are removed then and the path is smoothed at the turning points. That improved algorithm, in combination with distributed scroll algorithms, is applied to multi-robot path planning in an effort to optimize the path with the avoidance of collision. The experimental results on the 2D simulation platform have verified the feasibility of that method.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002