摘要
多机器人共同创建大规模地图,实现的关键在于机器人相对位置未知的情况下将多张局部栅格地图进行拼接。结合图像特征匹配的方法和改进的粒子群优化算法,先提取待拼接的两幅栅格地图的特征点进行匹配,并筛选有效特征点对;再将特征点对的信息作为改进的粒子群优化算法的输入参数,计算从源图像到目标图像的最佳转换矩阵;最后将转换后的源图像和目标图像使用栅格叠加的规则拼接在一起。通过仿真实验与数据分析,证明了算法的稳定性与准确性。
Multi robots create large-scale map together,the key of which is to splice multiple local grid maps when the relative position of robots is unknown.In this paper,the method of image feature matching and the improved particle swarm optimization algorithm are combined.Firstly,the feature points of the two grid maps to be spliced are extracted for matching,and the effective feature point pairs are screened.Then,the information of the feature point pairs is used as the input parameters of the improved particle swarm optimization algorithm to calculate the best conversion matrix from the source image to the destination image.Finally,the converted source image and destination image are stitched together by using the grid superposition rule.Through simulation experiments and data analysis,the stability and accuracy of the algorithm are proved.
作者
陈超
张志昂
丁丽君
Chen Chao;Zhang Zhiang;Ding Lijun(School of Mechanical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212000,China)
出处
《电子技术应用》
2020年第12期139-143,共5页
Application of Electronic Technique
基金
国家自然科学基金(51705217)。
