Earticle

초록

영어

Crowd animation is a new and continuous challenge in computer animation. In tradition, crowd animation can be realized by key frame technology, and animators should set every character’s expression, action, motion, and behavior. Therefore animators’ workload by hand will increase tremendously with characters growing, which lead to difficult to realize crowd animation for low efficiency and poor global controllability, especially in path planning by appointing a target position for each individuals. In order to overcome these, an improved artificial bee colony (IM-ABC) algorithm is proposed to apply on the path planning of crowd animation. The IM-ABC is fit to simulate the crowd motion in animation based on the following two merits over the others in crowd animation. One is the rule of role transformation, which can make the rapid convergence of the result and avoid getting trapped in the local optima. The other is the realization of multi-object optimization in the process of iteration, which reaches the uniformly distributed result of swarm motion and especially fits to realize the path plan. In this paper, we simply reviews classical ABC algorithm proposed by Karaboga at the beginning. Then, in order to speed the convergence and make individuals generate paths more realistic and natural, some measures are taken to modify the classical ABC (called IM-ABC) algorithm, which include initializing colony based on chaos sequence, self-adaptively selecting the follower bees, and adaptively controlling parameters, etc. After the experiments of benchmark functions, the results confirm that the IM-ABC have better performance than the classical ABC algorithm and others. Finally, the IM-ABC algorithm is used for path planning to generate the route from the initial to the destination without collision. Through simulation experiments based on four motion models it is showed that this method can succeed generating the optimum paths with efficiency, intelligence, and natural features.

목차

Abstract
 1. Introduction
 2. Related Work
 3. ABC Algorithm
 4. Improved Artificial Bee Colony Algorithm（IM-ABC Algorithm）
  4.1. Initialization of the ABC based on Chaos Sequence
  4.2. Self-adaptive Method to Select the Follower Bees
  4.3. Adaptive Parameter Control
  4.4. Flow Chart of the IM-ABC Algorithm
  4.5. Simulation of IM-ABC Algorithm
 5. Application on Path Planning of Crowd Animation
  5.1. Model of Crowd Motion
  5.2. Fitness Function
  5.3. Simulation Experiments
 6. Conclusion
 Acknowledgments
 References

키워드

저자

• Bai Jin [ Information Science and Engineering College Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology ]
• Liu Hong [ Information Science and Engineering College Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605