The integration of vision-based frameworks to achieve lunar robot applications faces numerous challenges such as terrain configuration or extreme lighting conditions. This paper presents a generic task pipeline using object detection, instance segmentation and grasp detection, that can be used for various applications by using the results of these vision-based systems in a different way. We achieve a rock stacking task on a non-flat surface in difficult lighting conditions with a very good success rate of 92%. Eventually, we present an experiment to assemble 3D printed robot components to initiate more complex tasks in the future.

翻译：将基于视觉的框架集成以实现月球机器人应用面临着诸多挑战，例如地形变化或极端光照条件。本文提出了一种通用任务流程，该流程利用目标检测、实例分割和抓取检测，通过以不同方式利用这些视觉系统的结果，可适用于多种应用。我们在非平坦表面且光照条件困难的情况下实现了岩石堆叠任务，成功率高达92%。最后，我们展示了一项组装3D打印机器人部件的实验，以期为未来更复杂的任务奠定基础。