# ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation

arXiv: https://arxiv.org/abs/2409.13682 · HTML: https://mlsanity.com/paper/2409.13682/

## Key facts

- Cited by 67 papers in the map (data through 14 Oct 2026).
- Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning.
- Builds on 47 of its 54 references that are in the map.
- First posted on arXiv 20 Sep 2024.

## Placed in

- LLM reasoning / [Spatial and embodied reasoning](https://mlsanity.com/lr/spatial-and-embodied-reasoning/)

## Builds on (most cited first, 30 of 47)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [Reflexion: Language Agents with Verbal Reinforcement Learning](https://mlsanity.com/paper/2303.11366/) (2023)
- [Toolformer: Language Models Can Teach Themselves to Use Tools](https://mlsanity.com/paper/2302.04761/) (2023)
- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://mlsanity.com/paper/2305.10601/) (2023)
- [Do As I Can, Not As I Say: Grounding Language in Robotic Affordances](https://mlsanity.com/paper/2204.01691/) (2022)
- [Retrieval-Augmented Generation for Large Language Models: A Survey](https://mlsanity.com/paper/2312.10997/) (2023)
- [Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection](https://mlsanity.com/paper/2310.11511/) (2023)
- [Ego4D: Around the World in 3,000 Hours of Egocentric Video](https://mlsanity.com/paper/2110.07058/) (2021)
- [Code as Policies: Language Model Programs for Embodied Control](https://mlsanity.com/paper/2209.07753/) (2022)
- [Inner Monologue: Embodied Reasoning through Planning with Language Models](https://mlsanity.com/paper/2207.05608/) (2022)
- [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://mlsanity.com/paper/1711.07280/) (2017)
- [VILA: On Pre-training for Visual Language Models](https://mlsanity.com/paper/2312.07533/) (2023)
- [ProgPrompt: Generating Situated Robot Task Plans using Large Language Models](https://mlsanity.com/paper/2209.11302/) (2022)
- [LLM+P: Empowering Large Language Models with Optimal Planning Proficiency](https://mlsanity.com/paper/2304.11477/) (2023)
- [LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action](https://mlsanity.com/paper/2207.04429/) (2022)
- [Object Goal Navigation using Goal-Oriented Semantic Exploration](https://mlsanity.com/paper/2007.00643/) (2020)
- [Embodied Question Answering](https://mlsanity.com/paper/1711.11543/) (2017)
- [NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Models](https://mlsanity.com/paper/2305.16986/) (2023)
- [Vision-and-Dialog Navigation](https://mlsanity.com/paper/1907.04957/) (2019)
- [Semi-parametric Topological Memory for Navigation](https://mlsanity.com/paper/1803.00653/) (2018)
- [Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions](https://mlsanity.com/paper/2004.03967/) (2020)
- [Search on the Replay Buffer: Bridging Planning and Reinforcement Learning](https://mlsanity.com/paper/1906.05253/) (2019)
- [CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation](https://mlsanity.com/paper/2203.10421/) (2022)
- [ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings](https://mlsanity.com/paper/2206.12403/) (2022)

## Built on by (most cited first, 30 of 67)

- [GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering](https://mlsanity.com/paper/2412.14480/) (2024)
- [The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break](https://mlsanity.com/paper/2604.11978/) (2026)
- [Show-Harness: Just a VLM Agent Can Play Robots](https://mlsanity.com/paper/2609.10522/) (2026)
- [Describe Anything Anywhere At Any Moment](https://mlsanity.com/paper/2512.00565/) (2025)
- [From Storage to Steering: Memory Control Flow Attacks on LLM Agents](https://mlsanity.com/paper/2603.15125/) (2026)
- [GAM: Hierarchical Graph-based Agentic Memory for LLM Agents](https://mlsanity.com/paper/2604.12285/) (2026)
- [LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics](https://mlsanity.com/paper/2504.21716/) (2025)
- [Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering](https://mlsanity.com/paper/2507.12846/) (2025)
- [Gated Memory Policy: In-Context Memorization and Adaptation](https://mlsanity.com/paper/2604.18933/) (2026)
- [CLiViS: Unleashing Cognitive Map through Linguistic-Visual Synergy for Embodied Visual Reasoning](https://mlsanity.com/paper/2506.17629/) (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)
- [Episodic memory in AI agents poses risks that should be studied and mitigated](https://mlsanity.com/paper/2501.11739/) (2025)
- [Goal2Skill: Long-Horizon Manipulation with Adaptive Planning and Reflection](https://mlsanity.com/paper/2604.13942/) (2026)
- [SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation](https://mlsanity.com/paper/2509.08757/) (2025)
- [Meta-Memory: Retrieving and Integrating Semantic-Spatial Memories for Robot Spatial Reasoning](https://mlsanity.com/paper/2509.20754/) (2025)
- [MANSION: Multi-floor lANguage-to-3D Scene generatIOn for loNg-horizon tasks](https://mlsanity.com/paper/2603.11554/) (2026)
- [Efficient Evaluation of Multi-Task Robot Policies With Active Experiment Selection](https://mlsanity.com/paper/2502.09829/) (2025)
- [From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model](https://mlsanity.com/paper/2605.22671/) (2026)
- [NL-Eye: Abductive NLI for Images](https://mlsanity.com/paper/2410.02613/) (2024)
- [EfficientNav: Towards On-Device Object-Goal Navigation with Navigation Map Caching and Retrieval](https://mlsanity.com/paper/2510.18546/) (2025)
- [Episodic Memory Verbalization using Hierarchical Representations of Life-Long Robot Experience](https://mlsanity.com/paper/2409.17702/) (2024)
- [OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism](https://mlsanity.com/paper/2603.14371/) (2026)
- [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)
- [HIMM: Human-Inspired Long-Term Memory Modeling for Embodied Exploration and Question Answering](https://mlsanity.com/paper/2602.15513/) (2026)
- [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)
- [Remember with Confidence: Uncertainty Quantification for Spatio-temporal Memory with Probabilistic Guarantees](https://mlsanity.com/paper/2606.08277/) (2026)

## Abstract (arXiv)

Navigating and understanding complex environments over extended periods of time is a significant challenge for robots. People interacting with the robot may want to ask questions like where something happened, when it occurred, or how long ago it took place, which would require the robot to reason over a long history of their deployment. To address this problem, we introduce a Retrieval-augmented Memory for Embodied Robots, or ReMEmbR, a system designed for long-horizon video question answering for robot navigation. To evaluate ReMEmbR, we introduce the NaVQA dataset where we annotate spatial, temporal, and descriptive questions to long-horizon robot navigation videos. ReMEmbR employs a structured approach involving a memory building and a querying phase, leveraging temporal information, spatial information, and images to efficiently handle continuously growing robot histories. Our experiments demonstrate that ReMEmbR outperforms LLM and VLM baselines, allowing ReMEmbR to achieve effective long-horizon reasoning with low latency. Additionally, we deploy ReMEmbR on a robot and show that our approach can handle diverse queries. The dataset, code, videos, and other material can be found at the following link: https://nvidia-ai-iot.github.io/remembr