一种高匹配性的多层代价地图生成算法  

A high matching layered costmap generation algorithm

作　　者：张福海[1] 王宇 薛铁刚 袁儒鹏 付宜利[1] ZHANG Fu-hai;WANG Yu;XUE Tie-gang;YUAN Ru-peng;FU Yi-li(The State Key Laboratory of Robotics and System,Harbin Institute of Technology,Harbin 150001,China)

机构地区：[1]哈尔滨工业大学机器人技术与系统国家重点实验室,哈尔滨150001

出　　处：《控制与决策》2020年第12期2883-2888,共6页Control and Decision

基　　金：黑龙江省自然科学基金项目(LC2017022)。

摘　　要：阐述目前代价地图中存在的相关问题,并针对代价地图存在匹配性差和实时性低等问题提出一种新的室内地图生成算法.首先,针对雷达对动态障碍物的处理方式,研究新的动态障碍物实时更新的方法,实现对障碍物的准确定位,改善代价地图与室内环境的匹配性;其次,通过预处理静态障碍物,实现对障碍物的分类以及分别处理,可大幅降低代价地图更新过程中的计算量,变相地提高代价地图的计算速度;再次,通过等距膨胀法构建完整的多层代价地图;最后,在实验室的自主机器人平台上进行实验,实验结果表明,所提出算法与经典代价地图算法相比在匹配性方面有明显提升,而在地图的更新速度方面平均提升77.6%.This paper discusses the related problems existing in the costmap,and proposes a new algorithm for the generation of indoor map.Firstly,for the processing method of dynamic obstacles by radar,a new real-time updating method of dynamic obstacles is studied,which realizes the accurate positioning of obstacles,and improves the matching of costmap and indoor environment.Then,the algorithm realizes the classification and separate processing of obstacles by preprocessing static obstacles,greatly reducing the cost in the process of map updating,the calculation speed of costmap is increased in a disguised way,and on this basis,a complete multi-layer costmap is constructed using the equidistant expansion method.Finally,the algorithm is tested on the autonomous robot platform.The experimental results show that the proposed algorithm has a significant improvement in matching compared with the classical costmap,and an average increase of 77.6%in map update speed.

关 键 词：机器人 雷达 代价地图 路径规划 机器人操作系统(ROS) 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]