# Last-Mile Embodied Visual Navigation

arXiv: https://arxiv.org/abs/2211.11746 · HTML: https://mlsanity.com/paper/2211.11746/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Builds on 64 of its 89 references that are in the map.
- First posted on arXiv 21 Nov 2022.

## Builds on (most cited first, 30 of 64)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Emerging Properties in Self-Supervised Vision Transformers](https://mlsanity.com/paper/2104.14294/) (2021)
- [Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems](https://mlsanity.com/paper/2005.01643/) (2020)
- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [Matterport3D: Learning from RGB-D Data in Indoor Environments](https://mlsanity.com/paper/1709.06158/) (2017)
- [SuperPoint: Self-Supervised Interest Point Detection and Description](https://mlsanity.com/paper/1712.07629/) (2017)
- [Habitat: A Platform for Embodied AI Research](https://mlsanity.com/paper/1904.01201/) (2019)
- [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://mlsanity.com/paper/1711.07280/) (2017)
- [ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras](https://mlsanity.com/paper/1610.06475/) (2016)
- [On Evaluation of Embodied Navigation Agents](https://mlsanity.com/paper/1807.06757/) (2018)
- [Gibson Env: Real-World Perception for Embodied Agents](https://mlsanity.com/paper/1808.10654/) (2018)
- [Object Goal Navigation using Goal-Oriented Semantic Exploration](https://mlsanity.com/paper/2007.00643/) (2020)
- [Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning](https://mlsanity.com/paper/1609.05143/) (2016)
- [DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames](https://mlsanity.com/paper/1911.00357/) (2019)
- [Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans](https://mlsanity.com/paper/2110.04994/) (2021)
- [Vision-and-Dialog Navigation](https://mlsanity.com/paper/1907.04957/) (2019)
- [ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation](https://mlsanity.com/paper/2007.04954/) (2020)
- [ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects](https://mlsanity.com/paper/2006.13171/) (2020)
- [Cognitive Mapping and Planning for Visual Navigation](https://mlsanity.com/paper/1702.03920/) (2017)
- [Stereo Magnification: Learning View Synthesis using Multiplane Images](https://mlsanity.com/paper/1805.09817/) (2018)
- [TEACh: Task-driven Embodied Agents that Chat](https://mlsanity.com/paper/2110.00534/) (2021)
- [Neural Topological SLAM for Visual Navigation](https://mlsanity.com/paper/2005.12256/) (2020)
- [Simple but Effective: CLIP Embeddings for Embodied AI](https://mlsanity.com/paper/2111.09888/) (2021)
- [BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments](https://mlsanity.com/paper/2108.03332/) (2021)
- [Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration](https://mlsanity.com/paper/2010.09890/) (2020)
- [Learning Exploration Policies for Navigation](https://mlsanity.com/paper/1903.01959/) (2019)
- [MultiON: Benchmarking Semantic Map Memory using Multi-Object Navigation](https://mlsanity.com/paper/2012.03912/) (2020)
- [Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments](https://mlsanity.com/paper/2109.15207/) (2021)
- [Interactive Gibson Benchmark (iGibson 0.5): A Benchmark for Interactive Navigation in Cluttered Environments](https://mlsanity.com/paper/1910.14442/) (2019)

## Built on by (most cited first, 25 of 25)

- [Affordances from Human Videos as a Versatile Representation for Robotics](https://mlsanity.com/paper/2304.08488/) (2023)
- [GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation](https://mlsanity.com/paper/2404.06609/) (2024)
- [PIRLNav: Pretraining with Imitation and RL Finetuning for ObjectNav](https://mlsanity.com/paper/2301.07302/) (2023)
- [OVRL-V2: A simple state-of-art baseline for ImageNav and ObjectNav](https://mlsanity.com/paper/2303.07798/) (2023)
- [Renderable Neural Radiance Map for Visual Navigation](https://mlsanity.com/paper/2303.00304/) (2023)
- [Navigating to Objects Specified by Images](https://mlsanity.com/paper/2304.01192/) (2023)
- [GaussNav: Gaussian Splatting for Visual Navigation](https://mlsanity.com/paper/2403.11625/) (2024)
- [Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations](https://mlsanity.com/paper/2507.00990/) (2025)
- [RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation](https://mlsanity.com/paper/2405.05792/) (2024)
- [FGPrompt: Fine-grained Goal Prompting for Image-goal Navigation](https://mlsanity.com/paper/2310.07473/) (2023)
- [SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts](https://mlsanity.com/paper/2412.05552/) (2024)
- [Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation](https://mlsanity.com/paper/2402.17587/) (2024)
- [MemoNav: Working Memory Model for Visual Navigation](https://mlsanity.com/paper/2402.19161/) (2024)
- [MOPA: Modular Object Navigation with PointGoal Agents](https://mlsanity.com/paper/2304.03696/) (2023)
- [PlaceNav: Topological Navigation through Place Recognition](https://mlsanity.com/paper/2309.17260/) (2023)
- [IGL-Nav: Incremental 3D Gaussian Localization for Image-goal Navigation](https://mlsanity.com/paper/2508.00823/) (2025)
- [Exploitation-Guided Exploration for Semantic Embodied Navigation](https://mlsanity.com/paper/2311.03357/) (2023)
- [NOLO: Navigate Only Look Once](https://mlsanity.com/paper/2408.01384/) (2024)
- [Wanderland: Geometrically Grounded Simulation for Open-World Embodied AI](https://mlsanity.com/paper/2511.20620/) (2025)
- [Unified Visuomotor Targets: Supervising VLAs Beyond Physical Actions](https://mlsanity.com/paper/2608.03563/) (2026)
- [Transformers for Image-Goal Navigation](https://mlsanity.com/paper/2405.14128/) (2024)
- [RSRNav: Reasoning Spatial Relationship for Image-Goal Navigation](https://mlsanity.com/paper/2504.17991/) (2025)
- [Harnessing Input-Adaptive Inference for Efficient VLN](https://mlsanity.com/paper/2508.09262/) (2025)
- [FeudalNav: A Simple Framework for Visual Navigation](https://mlsanity.com/paper/2602.06974/) (2026)
- [From Region Arrival to Instance-Level Grounding in Vision-and-Language Navigation](https://mlsanity.com/paper/2607.03792/) (2026)

## Abstract (arXiv)

Realistic long-horizon tasks like image-goal navigation involve exploratory and exploitative phases. Assigned with an image of the goal, an embodied agent must explore to discover the goal, i.e., search efficiently using learned priors. Once the goal is discovered, the agent must accurately calibrate the last-mile of navigation to the goal. As with any robust system, switches between exploratory goal discovery and exploitative last-mile navigation enable better recovery from errors. Following these intuitive guide rails, we propose SLING to improve the performance of existing image-goal navigation systems. Entirely complementing prior methods, we focus on last-mile navigation and leverage the underlying geometric structure of the problem with neural descriptors. With simple but effective switches, we can easily connect SLING with heuristic, reinforcement learning, and neural modular policies. On a standardized image-goal navigation benchmark (Hahn et al. 2021), we improve performance across policies, scenes, and episode complexity, raising the state-of-the-art from 45% to 55% success rate. Beyond photorealistic simulation, we conduct real-robot experiments in three physical scenes and find these improvements to transfer well to real environments.
