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Simulating collective transport of virtual ants.

Guo, S.H., Wang, M.L., Notman, G., Chang, J., Zhang, J. J. and Liao, M.H., 2017. Simulating collective transport of virtual ants. Computer Animation & Virtual Worlds, 28 (3-4), e1779.

Full text available as:

CASA_2017_paper_58.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1002/cav.1779


This paper simulates the behaviour of collective transport where a group of ants transports an object in a cooperative fashion. Different from humans, the task coordination of collective transport, with ants, is not achieved by direct communication between group individuals, but through indirect information transmission via mechanical movements of the object. This paper proposes a stochastic probability model to model the decision-making procedure of group individuals and trains a neural network via reinforcement learning to represent the force policy. Our method is scalable to different numbers of individuals and is adaptable to users' input, including transport trajectory, object shape, external intervention, etc. Our method can reproduce the characteristic strategies of ants, such as realign and reposition. The simulations show that with the strategy of reposition, the ants can avoid deadlock scenarios during the task of collective transport.

Item Type:Article
Group:Faculty of Media & Communication
ID Code:29461
Deposited By: Symplectic RT2
Deposited On:11 Jul 2017 11:31
Last Modified:14 Mar 2022 14:05


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