EARN

This is the code of Edge Accelerated Robot Navigation With Collaborative Motion Planning.

Preqrequisite

Please install the following libraries and packages first.

• Python >= 3.8
• CVXPY
• ROS Noetic
• Carla
• Carla-ROS-bridge

Note

We recommend using Python 3.8 and Conda to manage Python environments, as examples are based on CARLA.

Test Environment

• Ubuntu 20.04

Code Use

You can firstly install the package by running the commands below:

bash ./setup.sh

For standalone navigation, you can run the commands below:

cd $CARLA_ROOT
bash ./CarlaUE4.sh

./pdd_demo.sh

For multi-vehicle navigation, you can run the commands below:

cd $CARLA_ROOT
bash ./CarlaUE4.sh

./earn_demo.sh

Demo Video

earn_demo.mp4

Note

EARN is developed based on RDA-planner and rda_ros. You may want to see more information in RDA-planner and rda_ros

Parameters

PDD Configuration

Parameter	Type	Default Value	Description
~receding	int	15	Receding horizon parameter for MPC.
~iter_num	int	3	Number of iterations for the MPC solver.
~enable_reverse	bool	False	Enables reverse movement if set to True.
~sample_time	float	0.3	Sampling time interval for the MPC.
~process_num	int	4	Number of parallel processes for MPC computation.
~accelerated	bool	True	Enables accelerated computation in MPC.
~time_print	bool	False	Enables time logging for MPC operations.
~obstacle_order	bool	True	Determines if obstacle ordering by distance is applied.
~max_edge_num	int	4	Maximum number of edges to consider for obstacles.
~max_obs_num	int	4	Maximum number of obstacles to consider.
~goal_index_threshold	int	1	Threshold for goal index determination.
~iter_threshold	float	0.2	Iteration threshold for convergence in MPC.
~slack_gain	float	10	Gain for slack variables in MPC constraints.
~max_sd	float	1.0	Maximum safety distance.
~min_sd	float	0.1	Minimum safety distance.
~ws	float	0.2	Weight for the state in the cost function.
~wu	float	1.4	Weight for the control inputs in the cost function.
~ro1	float	0.1	Weight parameter for the first term in the cost function.
~ro2	float	0.1	Weight parameter for the second term in the cost function.
~pdd_en	bool	True	Enables penalty dual decomposition.
~edge_accelerate	bool	True	Enables edge collaboration.

MPS Configuration

Parameter	Type	Default Value	Description
~edge_position	list	[255, 172]	Position of edge server.
~coverage	int	500	Communication coverage of edge server.
~Cth	int	30	Maximum computation load in ms for the edge solver.
~receding	int	15	Receding horizon parameter for MPC.
~max_edge_num	int	4	Maximum number of edges to consider for obstacles.
~max_obs_num	int	4	Maximum number of obstacles to consider.

Paper Video

EARN_TMECH.mp4

Citation

If you find our work helpful in your research, please consider starring the repository and citing our work using the following BibTeX entries:

@ARTICLE{10601554,
  author={Li, Guoliang and Han, Ruihua and Wang, Shuai and Gao, Fei and Eldar, Yonina C. and Xu, Chengzhong},
  journal={IEEE/ASME Transactions on Mechatronics}, 
  title={Edge Accelerated Robot Navigation With Collaborative Motion Planning}, 
  year={2025},
  volume={30},
  number={2},
  pages={1166-1178},
  doi={10.1109/TMECH.2024.3419436}}

  @ARTICLE{10036019,
  author={Han, Ruihua and Wang, Shuai and Wang, Shuaijun and Zhang, Zeqing and Zhang, Qianru and Eldar, Yonina C. and Hao, Qi and Pan, Jia},
  journal={IEEE Robotics and Automation Letters}, 
  title={RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments}, 
  year={2023},
  volume={8},
  number={3},
  pages={1715-1722},
  doi={10.1109/LRA.2023.3242138}}

Acknowledgement

We would like to thank the authors and developers of the following projects. This project is built upon these great open-sourced projects.

• RDA-planner
• rda_ros
• Carla
• Carla-ROS-bridge

Authors

Guoliang Li

Ruihua Han

Shuai Wang