Nowadays, robots equipped with a single camera, such as micro aerial vehicles (MAVs), are easily found at affordable costs. They can be used in different tasks, including the building of 3D environment maps. For building such maps, monocular simultaneous localization and mapping (SLAM) methods are employed, which usually generate sparse or semi-dense representations that are ill-suited for navigation tasks. We propose a new 3D exploration approach that uses a monocular camera as the only source of information. Our approach transforms a point cloud generated by monocular SLAM into local volumetric maps. These maps are built using the lines-of-sight between points and keyframes, allowing the MAV to navigate safely through the environment. Goal poses are dynamically defined to guide the MAV to explore the environment while avoiding obstacles. Besides that, the proposed approach seeks to determine properly when the environment was entirely explored, preventing that MAV stops before cover all the environment or flies more that is needed. The effectiveness of the proposed approach is evaluated in experiments in two different indoor environments, and show that it is possible to explore an environment using only a MAV equipped with a single monocular camera.

如今，配备有单个摄像头的机器人（如微型飞行器（MAV））很容易找到，价格可承受。它们可以用于不同的任务，包括3D环境地图的构建。为了构建此类地图，采用了单眼同时定位和地图绘制（SLAM）方法，该方法通常会生成不适合导航任务的稀疏或半密集表示形式。我们提出了一种新的3D探索方法，该方法将单眼相机用作唯一的信息源。我们的方法将单眼SLAM生成的点云转换为局部体积图。这些地图是使用点和关键帧之间的视线构建的，从而允许MAV在环境中安全导航。动态定义目标姿势，以引导MAV避开障碍物探索环境。除此之外，提出的方法试图确定完全探索环境的时间，以防止MAV在覆盖所有环境之前停止飞行或飞行所需的更多时间。在两种不同的室内环境中的实验中评估了所提出方法的有效性，结果表明仅使用配备了单眼单眼相机的MAV即可探索环境。