无人机视觉SLAM协同建图与导航

doi:10.11947/j.AGCS.2020.20190145

摘要/Abstract

摘要： 地面机器人由于其工作空间的限制，对环境感知存在较大局限性，结合空中机器人在视角方面的优势，实现空地机器人协作是主流趋势。本文提出了一种基于无人机视觉SLAM的协同建图与导航方法，利用无人机空中视角带来的大范围环境感知能力，协助地面机器人快速构建环境模型，提高地面机器人在具有挑战性的未知环境中建图与导航能力。本文方法首先构建了一个显著闭合边界实时检测和跟踪线程，结合点、线特征以及显著闭合边界，提出一种视觉SLAM方法用于无人机空中建图，与传统方法相比，闭合边界的结合极大优化了建图的效果。其次，地面机器人根据无人机获得的初始全局地图自动规划全局路径，在移动过程中，利用搭载的激光传感器对无人机建的初始地图进行更新，并且对路径进行连续的重新规划，避免与障碍物发生碰撞。为了验证本文方法的可行性和先进性，分别进行了仿真试验和真实试验。试验结果表明，本文方法显著提高了建图效果，实现了协同建图与导航方法的完整过程，提高了地面机器人在具有挑战的未知区域中进行自主建图和导航的能力。但是本文方法在障碍物分布密集、地面高低起伏等复杂情况下效果不佳，且实现的二维导航局限性大，未来工作立足于融合激光雷达、IMU等多传感器，提高深度估计和位姿估计等任务效果用于构建精准的三维占据栅格地图，并进一步设计三维空间空地协同建图与导航的方法。

关键词: 空地协同, 无人机, 视觉SLAM, 显著闭合边界, 自主导航

Abstract: Due to the limitation of its working space, ground robots have great limitations on environmental perception. Combining the advantages of aerial robots in perspective, it is the mainstream trend to realize the collaboration of aerial and ground robots. This paper proposes a collaborative mapping and navigation scheme based on visual SLAM in UAV platform, which utilizes the wide-area perception capability brought by the aerial view of unmanned aerial vehicle, to assist the ground robot to construct the environmental model quickly and improve the ability of ground robots to map and navigate in challenging and unknown environments. This scheme first constructs a real-time detection and tracking thread for salient closed boundaries, and proposes a novel visual SLAM solution proposed for mapping of UAV with combining point, line features and salient closed boundaries. Compared with the traditional scheme, the combination of closed boundaries greatly optimizes the effect of mapping. Secondly, the ground robot automatically plans the global path according to the initial global map obtained by the aerial robot. During the moving process, the initial map from UAV is updated by using the mounted laser sensor on the ground one. And the continuous re-planning of the path enables the ground robot to avoid collisions with obstacles. In order to verify the feasibility and advancement of the proposed scheme, simulation experiments and real experiments were carried out respectively. The experimental results show that the proposed scheme significantly improves the mapping effect, realizes the whole process of collaborative navigation and mapping scheme, which improves the ability of ground robots to perform autonomous navigation and mapping in challenging unknown areas. However, the proposed method is not effective in complex situations such as dense obstacles distribution, high and low ground level, and the implementation of 2D navigation has large limitations. Based on the fusion of multi-sensors such as Lidar, IMU, etc.. Future work needs to improve the effect of tasks such as depth estimation and pose estimation to build accurate three-dimensional occupancy grid maps, and further designs a three-dimensional air-ground collaborative mapping and navigation scheme.

Key words: air-ground collaboration, unmanned aerial vehicle, visual SLAM, salient closed boundaries, autonomous navigation

中图分类号:

P227

王晨捷, 罗斌, 李成源, 王伟, 尹露, 赵青. 无人机视觉SLAM协同建图与导航[J]. 测绘学报, 2020, 49(6): 767-776.

WANG Chenjie, LUO Bin, LI Chengyuan, WANG Wei, YIN Lu, ZHAO Qing. The collaborative mapping and navigation based on visual SLAM in UAV platform[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(6): 767-776.

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