Abstract: Most swarm intelligence algorithms fall into local optimum easily, and convergence speed is very slow. By introducing Particle Swarm Optimization(PSO) algorithm into Artificial Bee Colony(ABC) algorithm, this paper proposes an improved path generation method for selection of the optimal target location and the path planning of particle individuals. The path data are imported into maya software to conduct simulation experiments, and the results show that the method can generate lifelike group animation and enhance animation production efficiency.

Key words: swarm intelligence, path planning, swarm animation, Particle Swarm Optimization(PSO) algorithm, Artificial Bee Colony(ABC) algorithm

摘要： 大多数群体智能算法容易陷入局部最优，且收敛速度较慢。为此，将粒子群优化算法引入人工蜂群算法中，提出一种改进的路径生成算法NewABC，实现最优目标位置的选取及粒子个体的路径规划。将该方法生成的路径数据导入maya三维动画制作软件中进行仿真实验，结果表明，该方法生成的群体动画效果逼真，动画创作效率有较大的提高。

关键词: 群体智能, 路径规划, 群体动画, 粒子群优化算法, 人工蜂群算法

CLC Number: 

• TP391