# Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation

arXiv: https://arxiv.org/abs/2409.18313 · HTML: https://mlsanity.com/paper/2409.18313/

## Key facts

- Cited by 44 papers in the map (data through 14 Oct 2026).
- Builds on 43 of its 56 references that are in the map.
- First posted on arXiv 26 Sep 2024.

## Builds on (most cited first, 30 of 43)

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://mlsanity.com/paper/2305.10601/) (2023)
- [OpenVLA: An Open-Source Vision-Language-Action Model](https://mlsanity.com/paper/2406.09246/) (2024)
- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [Survey of Hallucination in Natural Language Generation](https://mlsanity.com/paper/2202.03629/) (2022)
- [From Local to Global: A Graph RAG Approach to Query-Focused Summarization](https://mlsanity.com/paper/2404.16130/) (2024)
- [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://mlsanity.com/paper/1711.07280/) (2017)
- [ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks](https://mlsanity.com/paper/1912.01734/) (2019)
- [NExT-QA:Next Phase of Question-Answering to Explaining Temporal Actions](https://mlsanity.com/paper/2105.08276/) (2021)
- [Retrieval Augmentation Reduces Hallucination in Conversation](https://mlsanity.com/paper/2104.07567/) (2021)
- [Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI](https://mlsanity.com/paper/2109.08238/) (2021)
- [On Evaluation of Embodied Navigation Agents](https://mlsanity.com/paper/1807.06757/) (2018)
- [AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles](https://mlsanity.com/paper/1705.05065/) (2017)
- [Object Goal Navigation using Goal-Oriented Semantic Exploration](https://mlsanity.com/paper/2007.00643/) (2020)
- [Room-Across-Room: Multilingual Vision-and-Language Navigation with Dense Spatiotemporal Grounding](https://mlsanity.com/paper/2010.07954/) (2020)
- [Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning](https://mlsanity.com/paper/1609.05143/) (2016)
- [Visual Language Maps for Robot Navigation](https://mlsanity.com/paper/2210.05714/) (2022)
- [Embodied Question Answering](https://mlsanity.com/paper/1711.11543/) (2017)
- [REVERIE: Remote Embodied Visual Referring Expression in Real Indoor Environments](https://mlsanity.com/paper/1904.10151/) (2019)
- [Analyzing and Mitigating Object Hallucination in Large Vision-Language Models](https://mlsanity.com/paper/2310.00754/) (2023)
- [Benchmarking Large Language Models in Retrieval-Augmented Generation](https://mlsanity.com/paper/2309.01431/) (2023)
- [SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning](https://mlsanity.com/paper/2307.06135/) (2023)
- [NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Models](https://mlsanity.com/paper/2305.16986/) (2023)
- [PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs](https://mlsanity.com/paper/2402.07872/) (2024)
- [Hydra: A Real-time Spatial Perception System for 3D Scene Graph Construction and Optimization](https://mlsanity.com/paper/2201.13360/) (2022)
- [Agent AI: Surveying the Horizons of Multimodal Interaction](https://mlsanity.com/paper/2401.03568/) (2024)
- [CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory](https://mlsanity.com/paper/2210.05663/) (2022)
- [Open-vocabulary Queryable Scene Representations for Real World Planning](https://mlsanity.com/paper/2209.09874/) (2022)
- [PONI: Potential Functions for ObjectGoal Navigation with Interaction-free Learning](https://mlsanity.com/paper/2201.10029/) (2022)
- [FILM: Following Instructions in Language with Modular Methods](https://mlsanity.com/paper/2110.07342/) (2021)

## Built on by (most cited first, 30 of 44)

- [A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents](https://mlsanity.com/paper/2601.12538/) (2026)
- [GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering](https://mlsanity.com/paper/2412.14480/) (2024)
- [Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook](https://mlsanity.com/paper/2503.18016/) (2025)
- [3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model](https://mlsanity.com/paper/2505.22657/) (2025)
- [RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration](https://mlsanity.com/paper/2504.06994/) (2025)
- [NavRAG: Generating User Demand Instructions for Embodied Navigation through Retrieval-Augmented LLM](https://mlsanity.com/paper/2502.11142/) (2025)
- [Embodied Agents Meet Personalization: Investigating Challenges and Solutions Through the Lens of Memory Utilization](https://mlsanity.com/paper/2505.16348/) (2025)
- [Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering](https://mlsanity.com/paper/2507.12846/) (2025)
- [Memory-Centric Embodied Question Answering](https://mlsanity.com/paper/2505.13948/) (2025)
- [FindingDory: A Benchmark to Evaluate Memory in Embodied Agents](https://mlsanity.com/paper/2506.15635/) (2025)
- [Humanizing Machines: Rethinking LLM Anthropomorphism Through a Multi-Level Framework of Design](https://mlsanity.com/paper/2508.17573/) (2025)
- [Neural Brain: A Neuroscience-inspired Framework for Embodied Agents](https://mlsanity.com/paper/2505.07634/) (2025)
- [RAVEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation](https://mlsanity.com/paper/2509.23563/) (2025)
- [Meta-Memory: Retrieving and Integrating Semantic-Spatial Memories for Robot Spatial Reasoning](https://mlsanity.com/paper/2509.20754/) (2025)
- [From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model](https://mlsanity.com/paper/2605.22671/) (2026)
- [A Grounded Memory System For Smart Personal Assistants](https://mlsanity.com/paper/2505.06328/) (2025)
- [Chameleon: Control-Indexed Prospective Memory for Visuomotor Manipulation](https://mlsanity.com/paper/2603.24576/) (2026)
- [3D Scene Graphs: Open Challenges and Future Directions](https://mlsanity.com/paper/2606.19383/) (2026)
- [GraphPad: Inference-Time 3D Scene Graph Updates for Embodied Question Answering](https://mlsanity.com/paper/2506.01174/) (2025)
- [ELHPlan: Efficient Long-Horizon Task Planning for Multi-Agent Collaboration](https://mlsanity.com/paper/2509.24230/) (2025)
- [Affordance RAG: Hierarchical Multimodal Retrieval with Affordance-Aware Embodied Memory for Mobile Manipulation](https://mlsanity.com/paper/2512.18987/) (2025)
- [FocusGraph: Graph-Structured Frame Selection for Embodied Long Video Question Answering](https://mlsanity.com/paper/2603.04349/) (2026)
- [Stop Wandering: Efficient Vision-Language Navigation via Metacognitive Reasoning](https://mlsanity.com/paper/2604.02318/) (2026)
- [RANa: Retrieval-Augmented Navigation](https://mlsanity.com/paper/2504.03524/) (2025)
- [Multimodal Data Storage and Retrieval for Embodied AI: A Survey](https://mlsanity.com/paper/2508.13901/) (2025)
- [MosaicThinker: On-Device Visual Spatial Reasoning for Embodied AI via Iterative Construction of Space Representation](https://mlsanity.com/paper/2602.07082/) (2026)
- [ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models](https://mlsanity.com/paper/2605.10993/) (2026)
- [PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft](https://mlsanity.com/paper/2605.27762/) (2026)
- [CLOSER-VLN: Closed-Loop Self-Verified Retrieval-Augmented Reasoning for Aerial Vision-Language Navigation](https://mlsanity.com/paper/2606.28397/) (2026)
- [EmbodiedRSI: Active Continual Robot Learning Through Hypothesis-Guided Co-Evolution](https://mlsanity.com/paper/2610.10498/) (2026)

## Abstract (arXiv)

There is no limit to how much a robot might explore and learn, but all of that knowledge needs to be searchable and actionable. Within language research, retrieval augmented generation (RAG) has become the workhorse of large-scale non-parametric knowledge; however, existing techniques do not directly transfer to the embodied domain, which is multimodal, where data is highly correlated, and perception requires abstraction. To address these challenges, we introduce Embodied-RAG, a framework that enhances the foundational model of an embodied agent with a non-parametric memory system capable of autonomously constructing hierarchical knowledge for both navigation and language generation. Embodied-RAG handles a full range of spatial and semantic resolutions across diverse environments and query types, whether for a specific object or a holistic description of ambiance. At its core, Embodied-RAG's memory is structured as a semantic forest, storing language descriptions at varying levels of detail. This hierarchical organization allows the system to efficiently generate context-sensitive outputs across different robotic platforms. We demonstrate that Embodied-RAG effectively bridges RAG to the robotics domain, successfully handling over 250 explanation and navigation queries across kilometer-level environments, highlighting its promise as a general-purpose non-parametric system for embodied agents.