# NavTopo: Leveraging Topological Maps For Autonomous Navigation Of a Mobile Robot

arXiv: https://arxiv.org/abs/2410.11492 · HTML: https://mlsanity.com/paper/2410.11492/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 31 references that are in the map.
- First posted on arXiv 15 Oct 2024.

## Builds on (most cited first, 18 of 18)

- [Habitat: A Platform for Embodied AI Research](https://mlsanity.com/paper/1904.01201/) (2019)
- [ORB-SLAM: a Versatile and Accurate Monocular SLAM System](https://mlsanity.com/paper/1502.00956/) (2015)
- [DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras](https://mlsanity.com/paper/2108.10869/) (2021)
- [DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames](https://mlsanity.com/paper/1911.00357/) (2019)
- [Hydra: A Real-time Spatial Perception System for 3D Scene Graph Construction and Optimization](https://mlsanity.com/paper/2201.13360/) (2022)
- [MinkLoc3D: Point Cloud Based Large-Scale Place Recognition](https://mlsanity.com/paper/2011.04530/) (2020)
- [RTAB-Map as an Open-Source Lidar and Visual SLAM Library for Large-Scale and Long-Term Online Operation](https://mlsanity.com/paper/2403.06341/) (2024)
- [Topological Semantic Graph Memory for Image-Goal Navigation](https://mlsanity.com/paper/2209.08274/) (2022)
- [S-Graphs+: Real-time Localization and Mapping leveraging Hierarchical Representations](https://mlsanity.com/paper/2212.11770/) (2022)
- [Theta*: Any-Angle Path Planning on Grids](https://mlsanity.com/paper/1401.3843/) (2014)
- [Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps](https://mlsanity.com/paper/1709.05533/) (2017)
- [VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough](https://mlsanity.com/paper/2104.06800/) (2021)
- [A Unified Approach for Autonomous Volumetric Exploration of Large Scale Environments under Severe Odometry Drift](https://mlsanity.com/paper/2010.09859/) (2020)
- [Lifelong Topological Visual Navigation](https://mlsanity.com/paper/2110.08488/) (2021)
- [Evaluation of RGB-D SLAM in Large Indoor Environments](https://mlsanity.com/paper/2212.05980/) (2022)
- [Fast 3D Sparse Topological Skeleton Graph Generation for Mobile Robot Global Planning](https://mlsanity.com/paper/2208.04248/) (2022)
- [Enhancing exploration algorithms for navigation with visual SLAM](https://mlsanity.com/paper/2110.09156/) (2021)
- [PRISM-TopoMap: Online Topological Mapping with Place Recognition and Scan Matching](https://mlsanity.com/paper/2404.01674/) (2024)

## Abstract (arXiv)

Autonomous navigation of a mobile robot is a challenging task which requires ability of mapping, localization, path planning and path following. Conventional mapping methods build a dense metric map like an occupancy grid, which is affected by odometry error accumulation and consumes a lot of memory and computations in large environments. Another approach to mapping is the usage of topological properties, e.g. adjacency of locations in the environment. Topological maps are less prone to odometry error accumulation and high resources consumption, and also enable fast path planning because of the graph sparsity. Based on this idea, we proposed NavTopo - a full navigation pipeline based on topological map and two-level path planning. The pipeline localizes in the graph by matching neural network descriptors and 2D projections of the input point clouds, which significantly reduces memory consumption compared to metric and topological point cloud-based approaches. We test our approach in a large indoor photo-relaistic simulated environment and compare it to a metric map-based approach based on popular metric mapping method RTAB-MAP. The experimental results show that our topological approach significantly outperforms the metric one in terms of performance, keeping proper navigational efficiency.