https://github.com/dddmobilerobot/dddmr_navigation

DDDMR navigation is a navigation stack for mobile robot autonomously moving in 3D environment
https://github.com/dddmobilerobot/dddmr_navigation

3d-navigation autonomous-mobile-robots autonomous-navigation autonomous-robots mobile-robot mobile-robot-navigation mobile-robots move-base navigation navigation-stack

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DDDMR navigation is a navigation stack for mobile robot autonomously moving in 3D environment

• Host: GitHub
• URL: https://github.com/dddmobilerobot/dddmr_navigation
• Owner: dddmobilerobot
• License: bsd-3-clause
• Created: 2024-07-14T11:55:04.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-10-18T18:16:22.000Z (2 months ago)
• Last Synced: 2024-10-19T14:32:58.688Z (2 months ago)
• Topics: 3d-navigation, autonomous-mobile-robots, autonomous-navigation, autonomous-robots, mobile-robot, mobile-robot-navigation, mobile-robots, move-base, navigation, navigation-stack
• Language: Shell
• Homepage:
• Size: 35.2 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# dddmr_navigation ROS2

> [!IMPORTANT]

> This repo contains all necessary packages as submodules (see **src** directory):

> ```

> cd ~

> git clone https://github.com/dddmobilerobot/dddmr_navigation.git

> cd dddmr_navigation && git submodule init && git submodule update 

> ```

DDDMR navigation (3D Mobile Robot Navigation) is a navigation stack allows users to map, localize and autonomously navigate in 3D environments. 

 Detail 

Below figure shows the comparison between 2D navigation stack and DDD(3D) navigation.

Our stack is a total solution for a mobile platform to navigate in 3D environments. There are plenty advantages for choosing DDD navigation:

  

- The standard procedures of DDD mobile robots and 2D mobile robots are the same, make it easier for 2D navigation stack users to transit to DDD navigation without difficulties:

  1. Mapping and refined the map.

  2. Turn off mapping, use MCL to localize the robot by providing an initial pose.

  3. Provide a goal to the robot, the robot will calculate the global plan and avoid obstacles using local planner.

- DDD navigation is no longer suffered from terrain situations. For example, ramps in factories or wheelchair accessible.

- DDD navigation has been welled tested is many fields and is based on the cost-effective hardware, for example, 16 lines lidar, intel NUC/Jetson Orin Nano and consumer-grade imu. We are trying to make the solution as affordable as possible.



    



## Demonstrations of DDD navigation functions

  

    
3D mapping

    
3D global planning

  

  

    
3D local planning

    
3D navigation

  

  

    
Obstacle avoidance (annoying test)

    
Auto docking

  


## Robot platform

We have been intensively testing our navigation stack on the development platform and different outdoor areas. We also keep in mind that a cost-effective solution is our objective.

Our platform is composed of:

- A lidar with 16 lines (Leishen C16)

- intel NUC i7 with 8 GB memory (Now we are testing on Nvidia Jetson Orin Nano)

- MPU 9250 IMU

- Intel Realsense D435

- AgileX Scout Mini - we have retrofitted Scout Mini Odometry with [3D odometry](https://github.com/dddmobilerobot/dddmr_hardware)