Event-Grounding Graph: Unified Spatio-Temporal Scene Graph From Robotic Observations

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Authors: Phuoc Duc Nguyen, Francesco Verdoja, Ville Kyrki
Cited by: 0
References: 25

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