# Hydra-Multi: Collaborative Online Construction of 3D Scene Graphs with Multi-Robot Teams

arXiv: https://arxiv.org/abs/2304.13487 · HTML: https://mlsanity.com/paper/2304.13487/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2023.

## Built on by (most cited first, 21 of 21)

- [What Is The Best 3D Scene Representation for Robotics? From Geometric to Foundation Models](https://mlsanity.com/paper/2512.03422/) (2025)
- [EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents](https://mlsanity.com/paper/2410.22662/) (2024)
- [General Place Recognition Survey: Towards Real-World Autonomy](https://mlsanity.com/paper/2405.04812/) (2024)
- [Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering](https://mlsanity.com/paper/2507.12846/) (2025)
- [Air-Ground Collaboration for Language-Specified Missions in Unknown Environments](https://mlsanity.com/paper/2505.09108/) (2025)
- [KeySG: Hierarchical Keyframe-Based 3D Scene Graphs](https://mlsanity.com/paper/2510.01049/) (2025)
- [GaussianGraph: 3D Gaussian-based Scene Graph Generation for Open-world Scene Understanding](https://mlsanity.com/paper/2503.04034/) (2025)
- [SG-Reg: Generalizable and Efficient Scene Graph Registration](https://mlsanity.com/paper/2504.14440/) (2025)
- [Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs](https://mlsanity.com/paper/2506.07454/) (2025)
- [Pandora: Articulated 3D Scene Graphs from Egocentric Vision](https://mlsanity.com/paper/2603.28732/) (2026)
- [Aion: Towards Hierarchical 4D Scene Graphs with Temporal Flow Dynamics](https://mlsanity.com/paper/2512.11903/) (2025)
- [3D Scene Graphs: Open Challenges and Future Directions](https://mlsanity.com/paper/2606.19383/) (2026)
- [Self-Localized Collaborative Perception](https://mlsanity.com/paper/2406.12712/) (2024)
- [OpenObject-NAV: Open-Vocabulary Object-Oriented Navigation Based on Dynamic Carrier-Relationship Scene Graph](https://mlsanity.com/paper/2409.18743/) (2024)
- [Rheos: Modelling Continuous Motion Dynamics in Hierarchical 3D Scene Graphs](https://mlsanity.com/paper/2603.20239/) (2026)
- [Map Prediction and Generative Entropy for Multi-Agent Exploration](https://mlsanity.com/paper/2501.13189/) (2025)
- [SG-Tailor: Inter-Object Commonsense Relationship Reasoning for Scene Graph Manipulation](https://mlsanity.com/paper/2503.18988/) (2025)
- [OP3DSG: Open-Vocabulary Part-Aware 3D Scene Graph Generation for Real-World Environments](https://mlsanity.com/paper/2606.29786/) (2026)
- [Gaussian Semantic Field for One-shot LiDAR Global Localization](https://mlsanity.com/paper/2510.12101/) (2025)
- [Semantic Enrichment of CAD-Based Industrial Environments via Scene Graphs for Simulation and Reasoning](https://mlsanity.com/paper/2601.06415/) (2026)
- [MA3DSG: Multi-Agent 3D Scene Graph Generation for Large-Scale Indoor Environments](https://mlsanity.com/paper/2602.04152/) (2026)

## Abstract (arXiv)

3D scene graphs have recently emerged as an expressive high-level map representation that describes a 3D environment as a layered graph where nodes represent spatial concepts at multiple levels of abstraction (e.g., objects, rooms, buildings) and edges represent relations between concepts (e.g., inclusion, adjacency). This paper describes Hydra-Multi, the first multi-robot spatial perception system capable of constructing a multi-robot 3D scene graph online from sensor data collected by robots in a team. In particular, we develop a centralized system capable of constructing a joint 3D scene graph by taking incremental inputs from multiple robots, effectively finding the relative transforms between the robots' frames, and incorporating loop closure detections to correctly reconcile the scene graph nodes from different robots. We evaluate Hydra-Multi on simulated and real scenarios and show it is able to reconstruct accurate 3D scene graphs online. We also demonstrate Hydra-Multi's capability of supporting heterogeneous teams by fusing different map representations built by robots with different sensor suites.