基于局部子地图方法的多机器人主动同时定位与地图创建

研究了多机器人在未知环境下以主动的方式协作完成同时定位与地图创建（SLAM）的问题．引入局部子地图方法，由每个机器人建立自身周围局部区域的子地图，使多个机器人之间的地图创建相互独立，从而对全局环境的SLAM问题进行分解．而每个机器人在建立局部子地图时将主动SLAM问题转化为多目标优化问题；机器人选取最优的控制输入，使定位与地图创建的准确性、信息增益以及多机器人之间的协调关系得到综合优化．最后，通过扩展的卡尔曼滤波器（EKF）对子地图进行融合得到全局地图．仿真结果验证了该方法的有效性．

Multi-robot Active Simultaneous Localization and Mapping Based on Local Submap Approach

The cooperative simultaneous localization and mapping(SLAM) finished in an active way by multiple robots in unknown environment is investigated.Local submap strategy is introduced in which each robot carries out map building in the local area around itself so that it can build local submap independent of other robots,then the SLAM problem in global environment can be decomposed into multiple sub-problems.The problem of active SLAM is converted into that of multiobjective optimization when each robot builds ...