基于局部子图匹配的SLAM方法

A New Solution to SLAM Problem Based on Local Map Matching

  • 摘要: 针对现有的SLAM解决方法在机器人被“绑架”时失效的问题,提出了基于局部子图匹配的方法.该方法对现有的SLAM解决构架进行了改进,提出交点最优匹配的特征相关算法,并且将奇异值分解方法引入机器人定位.最后,在结构化环境下将本方法和基于扩展卡尔曼滤波器的方法进行比较,讨论了基于局部子图匹配的方法在结构化环境中解决机器人“绑架”问题的有效性和可行性.

     

    Abstract: For the kidnapped robot problem in which most current SLAM(simultaneous localization and map building) approaches are invalid,a new solution based on the matching of local sub-graphs is proposed.The presented approach improves the architecture of current SLAM problems,provides a new feature association algorithm based on optimized vertex matching,and introduces a singular value decomposition method into robot localization.In the end,the presented approach and the EKF(extended Kalman filtering) approach are compared in structured environment,and the discussion are made in the term of the feasibility and the effectiveness of this approach based on local sub-graph matching method for the kidnapped robot problem in structured environment.

     

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