As the application scenarios of mobile robots are getting more complex and challenging, scene understanding becomes increasingly crucial. A mobile robot that is supposed to operate autonomously in indoor environments must have precise knowledge about what objects are present, where they are, what their spatial extent is, and how they can be reached; i.e., information about free space is also crucial. Panoptic mapping is a powerful instrument providing such information. However, building 3D panoptic maps with high spatial resolution is challenging on mobile robots, given their limited computing capabilities. In this paper, we propose PanopticNDT - an efficient and robust panoptic mapping approach based on occupancy normal distribution transform (NDT) mapping. We evaluate our approach on the publicly available datasets Hypersim and ScanNetV2. The results reveal that our approach can represent panoptic information at a higher level of detail than other state-of-the-art approaches while enabling real-time panoptic mapping on mobile robots. Finally, we prove the real-world applicability of PanopticNDT with qualitative results in a domestic application.

翻译：随着移动机器人的应用场景日益复杂且充满挑战，场景理解变得愈发关键。一台需要在室内环境中自主运行的移动机器人，必须精确掌握环境中存在哪些物体、它们的位置、空间范围以及如何抵达这些信息；换言之，自由空间的信息同样至关重要。全景建图是提供此类信息的强大工具。然而，考虑到移动机器人有限的计算能力，构建具有高空间分辨率的三维全景地图仍具挑战性。本文提出PanopticNDT——一种基于占据栅格正态分布变换（NDT）建图的高效鲁棒全景建图方法。我们在公开数据集Hypersim和ScanNetV2上对所提方法进行评估。结果表明，相较于其他先进方法，我们的方法能以更高细节层次表示全景信息，同时实现移动机器人的实时全景建图。最后，我们通过家庭应用场景的定性结果验证了PanopticNDT在实际场景中的适用性。