PanopticNDT: Efficient and Robust Panoptic Mapping
This addresses the problem of scene understanding for mobile robots operating autonomously in complex indoor environments, offering an incremental improvement in efficiency and detail.
The paper tackles the challenge of building high-resolution 3D panoptic maps on mobile robots with limited computing power by proposing PanopticNDT, an efficient and robust approach based on occupancy NDT mapping. The results show it achieves higher detail than other state-of-the-art methods and enables real-time mapping on mobile robots.
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.