# UcoSLAM: Simultaneous Localization and Mapping by Fusion of KeyPoints and Squared Planar Markers

arXiv: https://arxiv.org/abs/1902.03729 · HTML: https://mlsanity.com/paper/1902.03729/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Feb 2019.

## Built on by (most cited first, 12 of 12)

- [Visual SLAM: What are the Current Trends and What to Expect?](https://mlsanity.com/paper/2210.10491/) (2022)
- [Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines](https://mlsanity.com/paper/2503.02955/) (2025)
- [Optimizing Fiducial Marker Placement for Improved Visual Localization](https://mlsanity.com/paper/2211.01513/) (2022)
- [vS-Graphs: Tightly Coupling Visual SLAM and 3D Scene Graphs Exploiting Hierarchical Scene Understanding](https://mlsanity.com/paper/2503.01783/) (2025)
- [3D Reconstruction and Alignment by Consumer RGB-D Sensors and Fiducial Planar Markers for Patient Positioning in Radiation Therapy](https://mlsanity.com/paper/2103.12162/) (2021)
- [Comparative Study of Visual SLAM-Based Mobile Robot Localization Using Fiducial Markers](https://mlsanity.com/paper/2309.04441/) (2023)
- [The Use of Multi-Scale Fiducial Markers To Aid Takeoff and Landing Navigation by Rotorcraft](https://mlsanity.com/paper/2309.08769/) (2023)
- [DeepArUco++: Improved detection of square fiducial markers in challenging lighting conditions](https://mlsanity.com/paper/2411.05552/) (2024)
- [Domain Adaptation of Networks for Camera Pose Estimation: Learning Camera Pose Estimation Without Pose Labels](https://mlsanity.com/paper/2111.14741/) (2021)
- [The Invisible Map: Visual-Inertial SLAM with Fiducial Markers for Smartphone-based Indoor Navigation](https://mlsanity.com/paper/2310.10862/) (2023)
- [Text-guided Zero-Shot Object Localization](https://mlsanity.com/paper/2411.11357/) (2024)
- [CHOW-SLAM: Compact Hybrid Representation with Complementary Overlap Window Optimization for RGB-D SLAM](https://mlsanity.com/paper/2608.01914/) (2026)

## Abstract (arXiv)

This paper proposes a novel approach for Simultaneous Localization and Mapping by fusing natural and artificial landmarks. Most of the SLAM approaches use natural landmarks (such as keypoints). However, they are unstable over time, repetitive in many cases or insufficient for a robust tracking (e.g. in indoor buildings). On the other hand, other approaches have employed artificial landmarks (such as squared fiducial markers) placed in the environment to help tracking and relocalization. We propose a method that integrates both approaches in order to achieve long-term robust tracking in many scenarios. Our method has been compared to the start-of-the-art methods ORB-SLAM2 and LDSO in the public dataset Kitti, Euroc-MAV, TUM and SPM, obtaining better precision, robustness and speed. Our tests also show that the combination of markers and keypoints achieves better accuracy than each one of them independently.