Title :
Animal group behavioral model with Evasion Mechanism
Author :
Zhiping Duan ; Xiaodong Gu
Author_Institution :
Dept. of Electron. Eng., Fudan Univ., Shanghai, China
Abstract :
Modeling behavioral mechanism of animal group promotes the development of group animation and other fields involving crowd simulation. This paper introduces a model to mimic behaviors of animal group. We proposes a swarming intelligence algorithm, Evasion Mechanism Artificial Fish School Algorithm (EM-AFSA) in our model, in which AFSA often focuses on optimization. The EM-AFSA introduces a new mechanism, i.e. evasion, which enables the group to avoid obstacles and collisions and to evade predation. It also includes flocking, foraging and tailgating. It is convenient to show the dynamic demonstration of our model and the model vividly mimics the real animal group behavior, which could potentially be used in designing group animation.
Keywords :
computer animation; EM-AFSA; animal group behavioral model; behavioral mechanism; crowd simulation; dynamic demonstration; evasion mechanism; evasion mechanism artificial fish school algorithm; mimic behaviors; real animal group behavior; swarming intelligence algorithm; Animals; Animation; Biological system modeling; Heuristic algorithms; Mathematical model; Particle swarm optimization; Solid modeling; EM-AFSA; evasion mechanism; group animation; group behavior; swarm intelligence algorithm;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889542