Unmanned Aerial Vehicles equipped with cameras can be used to automate image capture for generating 3D models via photogrammetry. Current methods rely on a single vehicle to capture images sequentially, or use pre-planned and heuristic imaging configurations. We seek to provide a multi-agent control approach to capturing the images required to 3D map a region. A photogrammetry cost function is formulated that captures the importance of sharing feature-dense areas across multiple images for successful photogrammetry reconstruction. A distributed second-order coverage controller is used to minimise this cost and move agents to an imaging configuration. This approach prioritises high quality images that are simultaneously captured, leading to efficient and scalable 3D mapping of a region. We demonstrate our approach with a hardware experiment, generating and comparing 3D reconstructions from image sets captured using our approach to those captured using traditional methods.

中文翻译：

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多智能体无人机摄影测量的二阶覆盖控制

配备摄像头的无人驾驶飞行器可用于自动捕获图像，以通过摄影测量生成 3D 模型。当前的方法依赖于单个车辆按顺序捕获图像，或使用预先计划和启发式成像配置。我们寻求提供一种多代理控制方法来捕获 3D 映射区域所需的图像。制定了摄影测量成本函数，它捕捉了在多个图像之间共享特征密集区域对于成功进行摄影测量重建的重要性。分布式二阶覆盖控制器用于最小化此成本并将代理移动到成像配置。这种方法优先考虑同时捕获的高质量图像，从而实现区域的高效且可扩展的 3D 映射。我们通过硬件实验展示了我们的方法，