# VDO-SLAM: A Visual Dynamic Object-aware SLAM System

arXiv: https://arxiv.org/abs/2005.11052 · HTML: https://mlsanity.com/paper/2005.11052/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2020.

## Built on by (most cited first, 30 of 40)

- [Robust Dynamic Radiance Fields](https://mlsanity.com/paper/2301.02239/) (2023)
- [ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild](https://mlsanity.com/paper/2207.09137/) (2022)
- [NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wild](https://mlsanity.com/paper/2405.18715/) (2024)
- [Deep Patch Visual SLAM](https://mlsanity.com/paper/2408.01654/) (2024)
- [MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization](https://mlsanity.com/paper/2101.06605/) (2021)
- [DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic Environments](https://mlsanity.com/paper/2209.08430/) (2022)
- [PVO: Panoptic Visual Odometry](https://mlsanity.com/paper/2207.01610/) (2022)
- [DAS3R: Dynamics-Aware Gaussian Splatting for Static Scene Reconstruction](https://mlsanity.com/paper/2412.19584/) (2024)
- [DF-VO: What Should Be Learnt for Visual Odometry?](https://mlsanity.com/paper/2103.00933/) (2021)
- [AirDOS: Dynamic SLAM benefits from Articulated Objects](https://mlsanity.com/paper/2109.09903/) (2021)
- [Advances in Inference and Representation for Simultaneous Localization and Mapping](https://mlsanity.com/paper/2103.05041/) (2021)
- [From SLAM to Situational Awareness: Challenges and Survey](https://mlsanity.com/paper/2110.00273/) (2021)
- [PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments](https://mlsanity.com/paper/2411.15800/) (2024)
- [DynaGSLAM: Real-Time Gaussian-Splatting SLAM for Online Rendering, Tracking, Motion Predictions of Moving Objects in Dynamic Scenes](https://mlsanity.com/paper/2503.11979/) (2025)
- [Semantic Visual Simultaneous Localization and Mapping: A Survey](https://mlsanity.com/paper/2209.06428/) (2022)
- [Indoor Navigation Assistance for Visually Impaired People via Dynamic SLAM and Panoptic Segmentation with an RGB-D Sensor](https://mlsanity.com/paper/2204.01154/) (2022)
- [DBA-Fusion: Tightly Integrating Deep Dense Visual Bundle Adjustment with Multiple Sensors for Large-Scale Localization and Mapping](https://mlsanity.com/paper/2403.13714/) (2024)
- [TwistSLAM: Constrained SLAM in Dynamic Environment](https://mlsanity.com/paper/2202.12384/) (2022)
- [Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines](https://mlsanity.com/paper/2503.02955/) (2025)
- [Lidar with Velocity: Correcting Moving Objects Point Cloud Distortion from Oscillating Scanning Lidars by Fusion with Camera](https://mlsanity.com/paper/2111.09497/) (2021)
- [GSLAMOT: A Tracklet and Query Graph-based Simultaneous Locating, Mapping, and Multiple Object Tracking System](https://mlsanity.com/paper/2408.09191/) (2024)
- [Dream-SLAM: Dreaming the Unseen for Active SLAM in Dynamic Environments](https://mlsanity.com/paper/2602.21967/) (2026)
- [Flow4DGS-SLAM: Optical Flow-Guided 4D Gaussian Splatting SLAM](https://mlsanity.com/paper/2604.22339/) (2026)
- [Embracing Dynamics: Dynamics-aware 4D Gaussian Splatting SLAM](https://mlsanity.com/paper/2504.04844/) (2025)
- [TwistSLAM++: Fusing multiple modalities for accurate dynamic semantic SLAM](https://mlsanity.com/paper/2209.07888/) (2022)
- [UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling](https://mlsanity.com/paper/2309.17036/) (2023)
- [Motion State: A New Benchmark Multiple Object Tracking](https://mlsanity.com/paper/2312.17641/) (2023)
- [CAD-SLAM: Consistency-Aware Dynamic SLAM with Dynamic-Static Decoupled Mapping](https://mlsanity.com/paper/2505.19420/) (2025)
- [ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos](https://mlsanity.com/paper/2509.17864/) (2025)
- [Jacobian Computation for Cumulative B-Splines on SE(3) and Application to Continuous-Time Object Tracking](https://mlsanity.com/paper/2201.10602/) (2022)

## Abstract (arXiv)

Combining Simultaneous Localisation and Mapping (SLAM) estimation and dynamic scene modelling can highly benefit robot autonomy in dynamic environments. Robot path planning and obstacle avoidance tasks rely on accurate estimations of the motion of dynamic objects in the scene. This paper presents VDO-SLAM, a robust visual dynamic object-aware SLAM system that exploits semantic information to enable accurate motion estimation and tracking of dynamic rigid objects in the scene without any prior knowledge of the objects' shape or geometric models. The proposed approach identifies and tracks the dynamic objects and the static structure in the environment and integrates this information into a unified SLAM framework. This results in highly accurate estimates of the robot's trajectory and the full SE(3) motion of the objects as well as a spatiotemporal map of the environment. The system is able to extract linear velocity estimates from objects' SE(3) motion providing an important functionality for navigation in complex dynamic environments. We demonstrate the performance of the proposed system on a number of real indoor and outdoor datasets and the results show consistent and substantial improvements over the state-of-the-art algorithms. An open-source version of the source code is available.