This is the source code for the algorithm Spherical Vector-based Particle Swarm Optimization (SPSO). The current implementation is for path planning of Unmanned Aerial Vehicles (UAV). However, it can be modified to apply to other path planning and optimization problems. Details of this algorithm can be found in the paper: Manh Duong Phung, Quang Phuc Ha, "Safety-enhanced UAV Path Planning with Spherical Vector-based Particle Swarm Optimization", Journal of Applied soft computing, vol. 107, pp. 107376, 2021. The paper was awarded 2023 Best Paper Award of the Applied Soft Computing journal. Link to the paper: https://doi.org/10.1016/j.asoc.2021.107376 and its preprint https://arxiv.org/pdf/2104.10033
To run the program, download all the source files and run "SPSO_MAIN.m" in MATLAB. The program may require installing the Curve Fitting Toolbox depending on your MATLAB version.
Another path planning algorithm that includes kinematic constraints of the UAV using Multi-objective Particle Swarm Optimization can be found here: https://github.com/duongpm/NMOPSO
Details of the algorithm are described in the paper: Thi Thuy Ngan Duong, Duy-Nam Bui, Manh Duong Phung, "Navigation variable-based multi-objective particle swarm optimization for UAV path planning with kinematic constraints", Journal of Neural Computing and Applications, 2025. Link to the paper: https://doi.org/10.1007/s00521-024-10945-1 and its preprint https://arxiv.org/pdf/2104.10033
A new update that calculates the dynamic constraint of the quadcopter UAV and includes it in the path planning using Multi-goal Rapidly Exploring Random Tree (RRT) can be found here: https://github.com/duongpm/multi-target_RRT. In addition, we used Bezier interpolation to smooth the path and proved that the resulting trajectory is collision-free.
Details of the algorithm are described in the paper: Thu Hang Khuat, Duy-Nam Bui, Hoa TT. Nguyen, Mien L. Trinh, Minh T. Nguyen Manh Duong Phung, "Multi-goal Rapidly Exploring Random Tree with Safety and Dynamic Constraints for UAV Cooperative Path Planning", IEEE Transactions on Vehicular Technology, 2025. Link to the paper: https://doi.org/10.1109/TVT.2025.3560658 and its preprint https://doi.org/10.48550/arXiv.2504.11823