Computer Engineering, Faculty of Technology and Center of Excellence Cognitive Interaction Technology, Bielefeld University, POB 10 01 31, 33501 Bielefeld, Germany.
J Theor Biol. 2012 Jul 21;305:118-30. doi: 10.1016/j.jtbi.2012.04.022. Epub 2012 Apr 24.
A model of visual navigation in ants is presented which is based on a simple network predicting the changes of a visual scene under translatory movements. The model contains two behavioral components: the acquisition of multiple snapshots in different orientations during a learning walk, and the selection of a movement direction by a scanning behavior where the ant searches through different headings. Both components fit with observations in experiments with desert ants. The model is in most aspects biologically plausible with respect to the equivalent neural networks, and it produces reliable homing behavior in a simulated environment with a complex random surface texture. The model is closely related to the algorithmic min-warping method for visual robot navigation which shows good homing performance in real-world environments.
提出了一种基于预测平移运动下视觉场景变化的简单网络的蚂蚁视觉导航模型。该模型包含两个行为成分：在学习行走过程中获取多个不同方向的快照，以及通过扫描行为选择运动方向，蚂蚁在不同的头部方向搜索。这两个组成部分都符合在沙漠蚂蚁实验中的观察结果。该模型在生物上与等效的神经网络在大多数方面都是合理的，并且在具有复杂随机表面纹理的模拟环境中产生可靠的归巢行为。该模型与视觉机器人导航的算法最小弯曲方法密切相关，该方法在真实环境中具有良好的归巢性能。
