基于改进粒子群的三维动画中群体路径规划

Group path planning in 3D animation based on improved particle swarm

针对群体运动轨迹需要满足一致性和保持个体独立性的较高要求,该文提出将粒子群算法进行改进并应用于三维群体动画角色的路径规划,生成个体的运动路径实现逼真的动画辅助设计。首先针对群体行为特征采用引力搜索算法对粒子群算法进行改进,以便解决粒子群算法易陷入局部最优而导致的搜索精度较低的问题,然后引入碰撞检测和碰撞避免方法,最后将算法得到的路径数据导入三维软件中进行碰撞检测和群聚测试,并验证了算法具有可行性。

In 3D animation,group intelligence algorithms are often required to control group behaviors,which can improve animation production efficiency and animation fidelity.However,group motion trajectories need to meet consistency and maintain individual independence,which has a higher impact on group intelligence algorithms.The particle swarm algorithm is an evolutionary computing technology that simulates the foraging behavior of birds,and it has high advantages.Therefore,this paper proposes to improve the particle swarm algorithm and applies it to the path planning of the three-dimensional group animation characters to generate individual motion paths to achieve realistic animation-aided design.First,the gravitational search algorithm is used to improve the particle swarm algorithm based on the group behavior characteristics,so as to solve the problem of low search accuracy caused by the particle swarm algorithm easily falling into the local optimum,and then the collision detection and collision avoidance methods are introduced,and finally the algorithm is obtained.The path data are imported into 3D software for collision and clustering tests,and the feasibility of the algorithm is verified.