Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
dddmr_navigation is the 3D navigation solution for mobile robots includes mapping/localization/perception/path planning/controller/navigation stack
| Date | Stars |
|---|---|
| 2026-07-24 | 492 |
| 2026-07-25 | 493 |
| 2026-07-28 | 494 |
| 2026-07-30 | 495 |
| 2026-08-11 | 506 |
| 2026-08-18 | 514 |
| 2026-08-19 | 517 |
| 2026-08-20 | 520 |
| 2026-08-21 | 522 |
| 2026-08-22 | 523 |
| 2026-08-23 | 524 |
| 2026-08-24 | 525 |
| 2026-08-25 | 527 |
| 2026-08-28 | 529 |
| 2026-08-30 | 530 |
| 2026-09-03 | 533 |
| 2026-09-04 | 535 |
| 2026-09-05 | 536 |
| 2026-09-06 | 538 |
| 2026-09-07 | 539 |
| 2026-09-09 | 540 |
| 2026-09-10 | 541 |
| 2026-09-11 | 545 |
| 2026-09-13 | 546 |
| 2026-09-14 | 549 |
| 2026-09-15 | 550 |
| 2026-09-16 | 551 |
| 2026-09-17 | 554 |
| 2026-09-18 | 556 |
| 2026-09-19 | 559 |
| 2026-09-20 | 562 |
Today
+3 stars today
This week
+16 stars this week
This month
+40 stars this month
Momentum
28.0
growth rate 2.93%/day
# 🤖 dddmr_navigation
## 🧪 Automated CI/CD & Multi-LiDAR Test Suite
Configuring 3D LiDARs with non-zero tilt angles (pitch/roll/yaw) is often a major headache for beginners—frequently causing corrupted maps, bad ground-plane filtering, or broken coordinate transforms.
Our latest release introduces an automated **CI/CD Test Suite** that verifies sensor configurations and navigation compatibility before deployment:
* **Angle & Pitch Validation:** Automatically tests flat, forward-tilted, and custom-angled LiDAR mount geometries.
* **TF & Point Cloud Accuracy:** Ensures spatial transforms, ground projection, and obstacle clearing remain consistent across mounting angles.
* **Beginner-Friendly Benchmarking:** Pre-configured test scenarios serve as reliable reference setups for custom robot builds.
### 🔗 Quick Links
- **Run Tests Locally:**
Found the details in our [CICD docs](https://github.com/dfl-rlab/dddmr_navigation/tree/main/CICD_setup#dddmr-lego-loam-ci)
<table align='center'>
<tr width="100%">
<td width="33%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/CICD_setup/airy_t45_2x.gif" width="256" height="157"/><p align='center'>Airy tilted 45 degree</p></td>
<td width="33%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/CICD_setup/c16_t0_2x.gif" width="256" height="157"/><p align='center'>C16 with no tilting</p></td>
<td width="33%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/CICD_setup/mid360_t180_2x.gif" width="256" height="157"/><p align='center'>Mid360 rolling 180</p></td>
</tr>
</table>
## 🚀 Go2 Simulator!
We’ve just integrated a Gazebo models using Unitree-go2 with the DDDMR Navigation Stack, unlocking true 3D navigation for simulation and testing. Using the latest quadruped robots go2 combined with our advanced stack, you can explore navigation capabilities that go far beyond traditional 2D navigation frameworks.
👉 Jump in, simulate, and experience features that Nav2 alone can’t achieve — multi-level mapping, ramp navigation, and obstacle handling in complex environments.
[👾 Let's play go2 using dddmr navigation](https://github.com/dfl-rlab/dddmr_navigation/tree/main/src/dddmr_beginner_guide)
<p align='center'>
<img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/dddmr_beginner_guide/3d_nav_gz.gif" width="700" height="420"/>
</p>
---
> [!NOTE]
> DDDMR Navigation Stack is designed to solve the issues that [Nav2](https://github.com/ros-navigation/navigation2) not able to handle: such as multi-layer floor mapping and localization, path planning in stereo structures and percption markings and clearings in a 3D point cloud map.
<table align='center'>
<tr width="100%">
<td width="40%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/dddmr_navigation/multilevel_map.gif" width="400" height="260"/><p align='center'>Multilevel map</p></td>
<td width="40%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/dddmr_navigation/obstacle_avoidance.gif" width="400" height="260"/><p align='center'>Obstacle avoidance on ramps</p></td>
</tr>
<tr width="100%">
<td width="40%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/dddmr_navigation/mapping_navigating.gif" width="400" height="260"/><p align='center'>Navigating while mapping</p></td>
<td width="40%"><img src="https://github.com/dfl-rlab/dddmr_documentation_materials/blob/main/dddmr_semantic_segmentation/dddmr_semantic_segmentation_to_pointcloud.gif" width="400" height="260"/><p align='center'>Semantic segmentation and navigation (stay tuned🔥)</p></td>
</tr>
</table>
DDDMR navigation (3D Mobile Robot Navigation) is a navigation stack allows users to map, localize and autonomously navigate in 3D environments.
Below figure shows the comparison between 2D navigation stack and DDD(3D) navigation.
Our stack is a total solutExcerpt of 8,011 characters
Read on GitHub
273
21
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a1985626e133b751, llm:Repository topics and description: '3d-navigation, mapping/localization/perception/path planning/controller/navigation stack, 3d-slam, mobile-robots, quadruped-robot, unitree-go2, deep-learning, yolo'. Readme describes 3D LiDAR, SLAM, mapping, localization, perception, path planning, controller, Gazebo simulator integration.
matched fp:a1985626e133b751, llm:Repository topics and description: '3d-navigation, mapping/localization/perception/path planning/controller/navigation stack, 3d-slam, mobile-robots, quadruped-robot, unitree-go2, deep-learning, yolo'. Readme describes 3D LiDAR, SLAM, mapping, localization, perception, path planning, controller, Gazebo simulator integration.
matched fp:a1985626e133b751, llm:Repository topics and description: '3d-navigation, mapping/localization/perception/path planning/controller/navigation stack, 3d-slam, mobile-robots, quadruped-robot, unitree-go2, deep-learning, yolo'. Readme describes 3D LiDAR, SLAM, mapping, localization, perception, path planning, controller, Gazebo simulator integration.