Safe Vector Field for Robot Navigation in n-Dimensions - IEEE RA-L 2026

This repository contains the source code and simulations for the paper:

Safe Vector Field for Robot Navigation in n-Dimensions
Published in IEEE Robotics and Automation Letters (RA-L), 2026
DOI: 10.1109/LRA.2026.3655306

Repository Structure

📁 safe_vf_maltab/

MATLAB simulations demonstrating safe vector field guidance algorithms for curve following with obstacle avoidance. Contains 8 different simulation scenarios ranging from 2D to 6D spaces, including a ball-and-plate control system.

See safe_vf_maltab/README.md for detailed setup instructions and simulation descriptions.

📁 robotarium/

Multi-robot coordination experiments using the Robotarium platform. Implements safe vector field guidance for coordinated curve-following with collision avoidance among multiple robots.

See robotarium/README.md for setup instructions and usage details.

📁 crazyflie-docker/

Docker environment and code for Crazyswarm experiments with Crazyflie nano-quadcopters. Contains ROS workspace for real-world aerial robot experiments.

See crazyflie-docker/README.md for installation and deployment instructions.

The approach has been validated through:

1. Extensive MATLAB simulations (safe_vf_maltab)
2. Multi-robot ground experiments (Robotarium)
3. Aerial robot experiments (Crazyflie quadcopters)

Citation

If you use this code in your research, please cite:

@ARTICLE{11358671,
  author={Nunes, Arthur H. D. and Gonçalves, Vinicius M. and Pimenta, Luciano C. A.},
  journal={IEEE Robotics and Automation Letters}, 
  title={Safe Vector Field for Robot Navigation in $n$-Dimensions}, 
  year={2026},
  volume={},
  number={},
  pages={1-8},
  keywords={Vectors;Robots;Safety;Navigation;Euclidean distance;Collision avoidance;Smoothing methods;Trajectory;Symbols;Quadrotors},
  doi={10.1109/LRA.2026.3655306}}

Dependencies and Acknowledgments

This work builds upon and utilizes the following platforms:

Robotarium

The multi-robot experiments leverage the Robotarium platform:

S. Wilson, P. Glotfelter, L. Wang, S. Mayya, G. Notomista, M. Mote, and M. Egerstedt, "The robotarium: Globally impactful opportunities, challenges, and lessons learned in remote-access, distributed control of multirobot systems," IEEE Control Systems Magazine, vol. 40, no. 1, pp. 26–44, 2020.

• Website: http://www.robotarium.gatech.edu
• GitHub: robotarium/robotarium-matlab-simulator

Crazyswarm

The aerial robot experiments use the Crazyswarm framework:

J. A. Preiss*, W. Honig*, G. S. Sukhatme, and N. Ayanian, "Crazyswarm: A large nano-quadcopter swarm," in IEEE International Conference on Robotics and Automation (ICRA), pp. 3299–3304, IEEE, 2017.

• GitHub: USC-ACTLab/crazyswarm
• Documentation: crazyswarm.readthedocs.io

Requirements

Software

• MATLAB (R2014b or higher) with Optimization Toolbox
• Docker (for Crazyswarm experiments)
• ROS (for quadcopter experiments)
• Python 3.x (for Crazyswarm)

Hardware (Optional)

• Robotarium access (for physical multi-robot experiments)
• Crazyflie 2.x quadcopters (for aerial experiments)
• Motion capture system (for indoor flight experiments)

Getting Started

1. Clone the repository:

   git clone git@github.com:ArthurHDN/ral2026.git
   cd ral2026
   git submodule update --init --recursive

2. Choose your platform:

   • For MATLAB simulations: Navigate to safe_vf_maltab/
   • For Robotarium experiments: Navigate to robotarium/
   • For Crazyflie experiments: Navigate to crazyflie-docker/

3. Follow the specific README in each subfolder for detailed setup and execution instructions.

License

This project is licensed under the MIT License - see the LICENSE file for details.