一种室内高动态环境的机器人定位方法

A Robot Localization Method in Indoor Dynamic Environment

该文提出一种能让机器人在室内动态环境中进行长时间稳定定位的方法。该方法既能实现对高动态物体的过滤又能实现半静态物体的更新,在去除动态物体对定位性能影响的同时还能利用半静态物体中提供的定位信息提高定位性能。把动态物体的处理分为高动态物体的滤除和半静态物体的更新两部分。对于高动态物体滤除,考虑到定位系统的特性,提出延迟对比法和跟踪法相结合的动态物体检测方法;对于半静态物体的更新,采用位姿图优化加栅格地图覆盖的方式实现地图的动态更新。两种方法的结合让机器人能实现在动态环境中的长时间稳定定位。经过一系列实验和一年的实际运行表明:该方法能实现机器人在动态环境中的长时间定位,克服高动态物体的影响,同时让机器人的地图始终保持和当前环境一致。

Localization is one of the core technologies for mobile robots to achieve full autonomous movement and is a prerequisite for other autonomous tasks.The robot working environment is dynamic in most cases,so the localization algorithm must overcome the effects of dynamic changes in the environment.The paper proposes a localization algorithm that allows the robot to perform robust and life-long localization in dynamic environment.The algorithm can not only filter out high-dynamic objects but also update semi-static object on the map at the same time,and it can also use the information provided in semi-static objects to improve localization performance.In this paper,the processing of dynamic objects is divided into two parts:filtering of high-dynamic objects and updating of semi-static objects.For high dynamic object filtering,a dynamic object detection method combining a delay comparison method and a tracking method is proposed by observing the characteristics of localization system;for the update of semi-static objects,this paper uses the pose graph optimization and occupancy map to implement the dynamic update of the map.The combination of the two methods allows the robot to achieve long-term stable localization in a dynamic environment.The experimental results demonstrate that the proposed method allows the robot to achieve long-term localization,overcome the effects of high-dynamic objects and keep the map always consistent with the environment.