We are happy to announce that we will be able to present our work on “Enhancing 3D Scene Graphs with Real-Time Room Classification” at ICRA 2025 in May in Atlanta, USA.
In recent years, 3D scene graphs have become a critical tool in robotics and computer vision for enabling systems to understand both the geometric and semantic aspects of their surroundings. These data structures represent spatial and semantic relationships between objects in a three-dimensional environment, supporting tasks like navigation, object manipulation, and scene understanding. Our presentation and the associated publication present a novel real-time pipeline for 3D scene graph generation that offers flexibility in image segmentation techniques while incorporating room classification that is based on a Random Forest model. Our work enables robots to dynamically update their understanding of complex and large-scale environments in real-time. We evaluate our approach systematically on a dataset and in a real-life experiment. The results demonstrate the capability of running our solution at over 10 Hz on an Nvidia Jetson AGX Orin SoC while also scaling favorably in larger environments. Our proposed room classification approach predicts classes with an average accuracy of 80%.
More information on the conference program can be found on the ICRA website at https://2025.ieee-icra.org/. We look forward to meet you there!