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中文摘要：
针对大规模的未知环境,在机器人中间件技术（RTM）框架下,提出了一种基于视觉特征的拓扑地图节点匹配方法,并结合局部扫描匹配策略,实现多机器人系统地图拼接.该方法首先建立主-辅结构的多机器人模型,利用改进的SP-2ATM算法建立未知环境的拓扑结构并增量式地创建地图.在此基础上,提出了融合尺度不变（SIFT）特征的分层拓扑地图结构,并结合迭代最近点算法来实现多机器人系统地图拼接.本文以RTM作为通讯平台,使系统具有较高的实时性、灵活性和鲁棒性.USARSim仿真平台与真实环境下的实验结果验证了所提方法的可行性与有效性.
英文摘要：
For large-scale unknown environments,a method of topological node matching based on visual feature is presented,and a local scan matching strategy is integrated to realize map merging for multi-robot system under RTM（robot technology middleware） framework.A main-auxiliary structure model of multiple robots is developed,and an improved SP-2ATM algorithm is adopted to incrementally constructing topological map in unknown environments.Based on this,the hierarchical topology structure including SIFT（scale-invariant feature transform） feature information is presented,which is combined with ICP（iterative closest point） algorithm to realize map merging of multi-robot systems.RTM is taken as communication platform to improve the realtime performance,flexibility and robustness of the system.Simulation on USARSim and experimental results in actual environments verify the effectiveness of the proposed method.
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