基于GIS和SLAM的机器人大范围环境自主导航

机器人自主导航技术的基础是其自定位能力,同时同步定位与建图(SLAM)是实现机器人自定位的重要方法。目前由于大规模SLAM技术发展的限制,机器人很难实现在大范围环境下进行建图和导航,并且尚没有结合SLAM和实际地理空间信息指导大范围机器人导航的完整自主导航系统。提出基于GIS和SLAM的机器人大范围环境自主导航方法,利用真实的城市空间路网信息,以地理信息系统(GIS)空间数据库的存储和计算能力为数据支撑,基于提出的大范围导航算法,实现了一套包含空间数据库、SLAM、导航算法的完整系统,具有良好的可复用性和可扩展性,符合实际生活场景,可以指导机器人进行大范围条件下的导航和建图行为。同时通过对机器人激光建图信息的存储,使得再次经过本区域的机器人可以在户外精确定位,实现在室外GPS缺失或误差条件下自身位置的修正。此外地图信息的存储可以实现多机器人对地图信息的复用,为多机器人的规划提供支撑。同时将人类世界的空间信息与机器人建图信息相结合,细化和丰富了原有的空间信息。

Autonomous navigation of robot in large scale environments based on GIS and SLAM

SLAM (simultaneous localization and mapping) is widely used for self localization of robot, which is a basis for autonomous navigation of it. In order to autonomously navigate in unknown environments, a robot has to move around and generate the environmental map while localizing itself. However, SLAM in large scale environments is still a challenging research topic, and there is no complete system been reported yet that integrates SLAM and geographic information in such environments. In this paper, we propose an autonomous navigation system consisting of a GIS (Geographic Information System) database, SLAM system, and path planning method. The system is based on the computing capability of the GIS database. It can provide navigation guidance for a robot in a large geographic space. It is highly reusable and extensible. Moreover, the mapping result can serve as the basis of re localization of a robot in the area even without a GPS sensor. Combining the geographic information and the mapping results of a robot is of great help for the robot to understand the environment, and in the meantime, to enrich the origin geographic information with more details.