Dynamic multi-colony ant cooperative optimization schemes for road image segmentation
多蚁群动态协作优化的道路图像分割算法

Road detection of 2-dimension images is a key problem in vision navigation of mobile robots.Based on the energy minimization function of image segmentation,a new vision energy minimization model is derived which can be solved conveniently by the iterative optimization of swarm intelligence.And a multi-colony ant based dynamic cooperation optimization strategy is proposed to implement the optimized road detection.According to the divide-and-conquer principle,each colony optimizes a sub-problem independently.Then,a set of information exchange strategies are proposed for adaptive dynamic cooperation between neighboring colonies to realize the global optimization of road detection.Compared with the Graph cut based road detection method,the proposed dynamic multi-colony ant cooperative optimization method not only has better detection performance,but also can detect arbitrary number of clusters.It can be applied to detect complex road scenes that obtain multiple types of road.