JI Jia-wen,YANG Ming-xin.A Indoor Mapping and Localization Algorithm based on Multi-sensor Fusion[J].Journal of Chengdu University of Information Technology,2018,(04):400-407.[doi:10.16836/j.cnki.jcuit.2018.04.009]
一种基于多传感融合的室内建图和定位算法
- Title:
- A Indoor Mapping and Localization Algorithm based on Multi-sensor Fusion
- 文章编号:
- 2096-1618(2018)04-0400-08
- Keywords:
- multi-sensor fusion; lidar; loop-closure detection; graph-optimization; low-power consumption
- 分类号:
- TP242.6
- 文献标志码:
- A
- 摘要:
- 近年来,具备导航规划能力的自主移动机器人在各种领域广泛应用。而地图构建和定位(simultaneous localization and mapping,SLAM)是自主移动机器人的关键技术之一,它是清洁机器人、服务机器人、AGV机器人等自主导航的重要保障。在动态、复杂的商场,长走廊等室内应用场景中,自主机器人必须准确地定位自己所处的位置,并避开障碍物,完成设定的任务。自主机器人在这些复杂场景中,往往需要价格高昂、远距离测距的激光雷达感知环境。提出的算法主要针对低成本的激光雷达,采用了多传感数据融合技术,利用IMU,编码器信息进行融合,准确地估计轮式机器人的位姿,并在此估计的位姿上,通过将激光雷达的点云匹配得到环境的概率栅格地图。与此同时,后端闭环检测加入闭环约束条件,并利用图优化方法消除前端构建地图时的累积误差,从而使轮式机器人能够在大场景和长走廊场景下构建精度很好的环境地图,最后基于良好的建图,解决机器人的全局定位问题。该基于多传感融合的建图和定位算法,具有实时,低功耗,鲁棒性好的优点,并且在资源有限的嵌入式平台上运行也得到很好的结果。
- Abstract:
- In recent years, autonomous mobile robots with the ability of navigation and planning have been widely applied in various fields. SLAM(Simultaneous Localization And Mapping)is one of the core technologies for autonomous mobile robots, which is a important guarant for cleaning robots, service robots, AGV robots other indoor scenarios. In dynamic and complex indoor application scenarios, such as offices and shopping malls, autonomous robots must accurately know their location and avoid obstacles to complete the assigned tasks. Autonomous robots often require a perception of environment with expensive, long-distance range of lidar in these complex scene. The algorithm proposed in this paper is mainly aimed at low-cost lidar, using multi-sensor data fusion technology, and estimates the accurate pose of a wheeled robot by integrating the information of the encoder and low-cost IMU. And it constructs the probability grid map of indoor environment by matching the lidar’s scans. At the same time, this algorithm adds the constraint of loop closure in the back-end when the loop closure appears, and eliminates all the cumulative errors of mapping by the optimization method. It leads to a environment map with good precision for a wheeled robot and a solution for global localization based on the map.The multi-sensor fusion algorithm proposed in this paper has the advantages of real-time, low-power consumption, robustness and it can obtain a good result on the embedded platform with limited resources.
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备注/Memo
收稿日期:2018-05-02