Event-Grounding Graph: Unified Spatio-Temporal Scene Graph From Robotic Observations
Abstract
A fundamental aspect for building intelligent autonomous robots that can assist humans in their daily lives is the construction of rich environmental representations. While advances in semantic scene representations have enriched robotic scene understanding, current approaches lack a connection between spatial features and dynamic events;e.g., connectingthe blue mugto the eventwashing a mug. In this work, we introduce event-grounding graph (EGG), a framework grounding event interactions to spatial features of a scene. This representation allows robots to perceive, reason, and respond to complex spatio-temporal queries. Experiments using real robotic data demonstrate EGG's capability to retrieve relevant information and respond accurately to human inquiries concerning the environment and events within. Furthermore, the EGG framework's source code and evaluation dataset are released as open-source at:https://github.com/aalto-intelligent-robotics/EGG.
Fields of Study & Subjects
Multimodal Machine Learning Applications
Robotics and Sensor-Based Localization
Autonomous Vehicle Technology and Safety
Publication details
- Journal / source
- IEEE Robotics and Automation Letters
- Volume
- 11
- Issue
- 5
- Pages
- 5286–5293
- Publication date
- 2 March 2026
- Language
- EN