# Advancing Audio-Visual Navigation Through Multi-Agent Collaboration in 3D Environments

arXiv: https://arxiv.org/abs/2509.22698 · HTML: https://mlsanity.com/paper/2509.22698/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 32 references that are in the map.
- First posted on arXiv 21 Sep 2025.

## Builds on (most cited first, 27 of 27)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Matterport3D: Learning from RGB-D Data in Indoor Environments](https://mlsanity.com/paper/1709.06158/) (2017)
- [The Replica Dataset: A Digital Replica of Indoor Spaces](https://mlsanity.com/paper/1906.05797/) (2019)
- [Multiagent Cooperation and Competition with Deep Reinforcement Learning](https://mlsanity.com/paper/1511.08779/) (2015)
- [Vision-Language Navigation with Self-Supervised Auxiliary Reasoning Tasks](https://mlsanity.com/paper/1911.07883/) (2019)
- [ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments](https://mlsanity.com/paper/2304.03047/) (2023)
- [Multi-Agent Reinforcement Learning is a Sequence Modeling Problem](https://mlsanity.com/paper/2205.14953/) (2022)
- [Towards Learning a Generalist Model for Embodied Navigation](https://mlsanity.com/paper/2312.02010/) (2023)
- [Discuss Before Moving: Visual Language Navigation via Multi-expert Discussions](https://mlsanity.com/paper/2309.11382/) (2023)
- [Look, Listen, and Act: Towards Audio-Visual Embodied Navigation](https://mlsanity.com/paper/1912.11684/) (2019)
- [Structured Scene Memory for Vision-Language Navigation](https://mlsanity.com/paper/2103.03454/) (2021)
- [SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning](https://mlsanity.com/paper/2206.08312/) (2022)
- [Affordances-Oriented Planning using Foundation Models for Continuous Vision-Language Navigation](https://mlsanity.com/paper/2407.05890/) (2024)
- [MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation](https://mlsanity.com/paper/2502.13451/) (2025)
- [Sound Adversarial Audio-Visual Navigation](https://mlsanity.com/paper/2202.10910/) (2022)
- [Two Body Problem: Collaborative Visual Task Completion](https://mlsanity.com/paper/1904.05879/) (2019)
- [Learning in Audio-visual Context: A Review, Analysis, and New Perspective](https://mlsanity.com/paper/2208.09579/) (2022)
- [Reinforced Structured State-Evolution for Vision-Language Navigation](https://mlsanity.com/paper/2204.09280/) (2022)
- [Move2Hear: Active Audio-Visual Source Separation](https://mlsanity.com/paper/2105.07142/) (2021)
- [Vision-Language Navigation: A Survey and Taxonomy](https://mlsanity.com/paper/2108.11544/) (2021)
- [Audio Visual Language Maps for Robot Navigation](https://mlsanity.com/paper/2303.07522/) (2023)
- [AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments](https://mlsanity.com/paper/2210.07940/) (2022)
- [Measuring Acoustics with Collaborative Multiple Agents](https://mlsanity.com/paper/2310.05368/) (2023)
- [Omnidirectional Information Gathering for Knowledge Transfer-based Audio-Visual Navigation](https://mlsanity.com/paper/2308.10306/) (2023)
- [WebVLN: Vision-and-Language Navigation on Websites](https://mlsanity.com/paper/2312.15820/) (2023)
- [Pay Self-Attention to Audio-Visual Navigation](https://mlsanity.com/paper/2210.01353/) (2022)
- [DOPE: Dual Object Perception-Enhancement Network for Vision-and-Language Navigation](https://mlsanity.com/paper/2505.00743/) (2025)

## Built on by (most cited first, 14 of 14)

- [Parse, Search, and Confirmation: Training-Free Aerial Vision-and-Dialog Navigation with Chain-of-Thought Reasoning and Structured Spatial Memory](https://mlsanity.com/paper/2607.11529/) (2026)
- [Audio Spatially-Guided Fusion for Audio-Visual Navigation](https://mlsanity.com/paper/2604.02389/) (2026)
- [Spatial-Aware Conditioned Fusion for Audio-Visual Navigation](https://mlsanity.com/paper/2604.02390/) (2026)
- [Reliability-Aware Geometric Fusion for Robust Audio-Visual Navigation](https://mlsanity.com/paper/2604.02391/) (2026)
- [Generalizable Audio-Visual Navigation via Binaural Difference Attention and Action Transition Prediction](https://mlsanity.com/paper/2604.05007/) (2026)
- [EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence](https://mlsanity.com/paper/2604.23325/) (2026)
- [ML-SAN: Multi-Level Speaker-Adaptive Network for Emotion Recognition in Conversations](https://mlsanity.com/paper/2604.25383/) (2026)
- [Cross-Modal Navigation with Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2605.06595/) (2026)
- [HRO: Hierarchical Room-to-Object Framework for Zero-Shot Object Goal Navigation with Large Language Models](https://mlsanity.com/paper/2607.13072/) (2026)
- [CTAN: Cycle-Temporal Attention Network for Embodied Audio-Visual Navigation](https://mlsanity.com/paper/2609.17420/) (2026)
- [Transformer-Based Token Fusion and Dynamic Graph Planning for Audio-Visual Navigation](https://mlsanity.com/paper/2609.17421/) (2026)
- [Talking Head Synthesis with Facial Landmark Guidance via 3D Gaussian Splatting](https://mlsanity.com/paper/2609.17422/) (2026)
- [WS-NeRF: A Mamba-Driven World-State-Aware Adaptive Deblurring Neural Radiance Field](https://mlsanity.com/paper/2609.21391/) (2026)
- [Two-Stage Multi-modal Learning for Dynamic Audio-Visual Navigation: From Physical Alignment to Scene Aggregation](https://mlsanity.com/paper/2610.14077/) (2026)

## Abstract (arXiv)

Intelligent agents often require collaborative strategies to achieve complex tasks beyond individual capabilities in real-world scenarios. While existing audio-visual navigation (AVN) research mainly focuses on single-agent systems, their limitations emerge in dynamic 3D environments where rapid multi-agent coordination is critical, especially for time-sensitive applications like emergency response. This paper introduces MASTAVN (Multi-Agent Scalable Transformer Audio-Visual Navigation), a scalable framework enabling two agents to collaboratively localize and navigate toward an audio target in shared 3D environments. By integrating cross-agent communication protocols and joint audio-visual fusion mechanisms, MASTAVN enhances spatial reasoning and temporal synchronization. Through rigorous evaluation in photorealistic 3D simulators (Replica and Matterport3D), MASTAVN achieves significant reductions in task completion time and notable improvements in navigation success rates compared to single-agent and non-collaborative baselines. This highlights the essential role of spatiotemporal coordination in multi-agent systems. Our findings validate MASTAVN's effectiveness in time-sensitive emergency scenarios and establish a paradigm for advancing scalable multi-agent embodied intelligence in complex 3D environments.