# Deployment and Implementation of RDA\_planner

**URL:** <https://discourse.openrobotics.org/t/deployment-and-implementation-of-rda-planner/51956>\
**Category:** ROS General\
**Created:** [January 21, 2026, 8:12am UTC](https://discourse.openrobotics.org/t/deployment-and-implementation-of-rda-planner/51956 "2026-01-21T08:12:34Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Agilex\_Robotics](https://sea2.discourse-cdn.com/flex022/user_avatar/discourse.openrobotics.org/agilex_robotics/32/10554_2.png) [@Agilex\_Robotics](https://discourse.openrobotics.org/u/Agilex_Robotics)\
**Post date:** [January 21, 2026, 8:12am UTC](https://discourse.openrobotics.org/t/deployment-and-implementation-of-rda-planner/51956/1 "2026-01-21T08:12:34Z")

</div>

# Deployment and Implementation of RDA\_planner

We reproduce the RDA Planner project from the IEEE paper _RDA: An Accelerated Collision-Free Motion Planner for Autonomous Navigation in Cluttered Environments_. We provide a step-by-step guide to help you quickly reproduce the RDA path planning algorithm in this paper, enabling efficient obstacle avoidance for autonomous navigation in complex environments.

## Abstract

RDA Planner is a high-performance, optimization-based Model Predictive Control (MPC) motion planner designed for autonomous navigation in complex and cluttered environments. By leveraging the Alternating Direction Method of Multipliers (ADMM), RDA decomposes complex optimization problems into several simple subproblems.

This project is the open-source development of the RDA\_ROS autonomous navigation project, proposed by researchers from the University of Hong Kong, Southern University of Science and Technology, University of Macau, Shenzhen Institutes of Advanced Technology of the Chinese Academy of Sciences, and Hong Kong University of Science and Technology (Guangzhou). It is developed based on the AgileX Limo simulator. Relevant papers have been published in _IEEE Robotics and Automation Letters_ and _IEEE Transactions on Mechatronics_.

RDA planner: [GitHub - hanruihua/RDA-planner: [RA-Letter 2023] RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments](https://github.com/hanruihua/RDA-planner)  
RDA\_ROS: [GitHub - hanruihua/rda\_ros: ROS Wrapper of RDA planner](https://github.com/hanruihua/rda_ros)

## Tags

limo、RDA\_planner、path planning

## Respositories

- **Navigation Repository** : [GitHub - agilexrobotics/Agilex-College: Agilex College](https://github.com/agilexrobotics/Agilex-College)
- **Project Repository** : [https://github.com/agilexrobotics/limo/RDA\_planner.git](https://github.com/agilexrobotics/limo/RDA_planner.git)

## Environment Requirements

System：ubuntu 20.04

ROS Version：noetic

python Version：python3.9

## Deployment Process

1、Download and Install Conda

[Download Link](https://www.anaconda.com/download/success)

Choose Anaconda or Miniconda based on your system storage capacity

 ![img_1](https://us1.discourse-cdn.com/flex022/uploads/ros/original/3X/6/1/614bde8ec77e0cbeb604f14129d1325584e76013.png)

After downloading, run the following commands to install:

- Miniconda:

- Anaconda:

2、Create and Activate Conda Environment

```python
conda create -n rda python=3.9
conda activate rda

```

3、Download RDA\_planner

```python
mkdir -p ~/rda_ws/src
cd ~/rda_ws/src
git clone https://github.com/hanruihua/RDA_planner
cd RDA_planner
pip install -e .  

```

4、Download Simulator

```python
pip install ir-sim

```

5、Run Examples in RDA\_planner

```python
cd RDA_planner/example/lidar_nav
python lidar_path_track_diff.py

```

The running effect is consistent with the official README.

![img_2](https://us1.discourse-cdn.com/flex022/uploads/ros/original/3X/d/3/d33dec3d2580367252d617cdb5eb128750d4cb63.gif)

# Deployment Process of rda\_ros

1、Install Dependencies in Conda Environment

```python
conda activate rda
sudo apt install python3-empy
sudo apt install ros-noetic-costmap-converter
pip install empy==3.3.4
pip install rospkg
pip install catkin_pkg

```

2、Download Code

```python
cd ~/rda_ws/src
git clone https://github.com/hanruihua/rda_ros
cd ~/rda_ws && catkin_make
cd ~/rda_ws/src/rda_ros 
sh source_setup.sh && source ~/rda_ws/devel/setup.sh && rosdep install rda_ros 

```

3、Download Simulation Components

This step will download two repositories: `limo_ros` and `rvo_ros`

limo\_ros：Robot model for simulation

rvo\_ros：Cylindrical obstacles used in the simulation environment

```python
cd rda_ros/example/dynamic_collision_avoidance
sh gazebo_example_setup.sh

```

4、Run Gazebo Simulation

**Run via Script**

```python
cd rda_ros/example/dynamic_collision_avoidance
sh run_rda_gazebo_scan.sh

```

**Run via Individual Commands**

Launch the simulation environment:

```auto
roslaunch rda_ros gazebo_limo_env10.launch

```

Launch RDA\_planner

```auto
roslaunch rda_ros rda_gazebo_limo_scan.launch

```

![img_3](https://us1.discourse-cdn.com/flex022/uploads/ros/original/3X/1/c/1ce03d7016a907ab914d5a2eca9f140692eaa98f.gif)