# Angle-Encoded Swarm Optimization for UAV Formation Path Planning

arXiv: https://arxiv.org/abs/1812.07873 · HTML: https://mlsanity.com/paper/1812.07873/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Dec 2018.

## Built on by (most cited first, 4 of 4)

- [Safety-enhanced UAV Path Planning with Spherical Vector-based Particle Swarm Optimization](https://mlsanity.com/paper/2104.10033/) (2021)
- [Navigation Variable-based Multi-objective Particle Swarm Optimization for UAV Path Planning with Kinematic Constraints](https://mlsanity.com/paper/2501.03261/) (2025)
- [Ant Colony Optimization for Cooperative Inspection Path Planning Using Multiple Unmanned Aerial Vehicles](https://mlsanity.com/paper/2402.08246/) (2024)
- [Enhancing Swarms Durability to Threats via Graph Signal Processing and GNN-based Generative Modeling](https://mlsanity.com/paper/2507.03039/) (2025)

## Abstract (arXiv)

This paper presents a novel and feasible path planning technique for a group of unmanned aerial vehicles (UAVs) conducting surface inspection of infrastructure. The ultimate goal is to minimise the travel distance of UAVs while simultaneously avoid obstacles, and maintain altitude constraints as well as the shape of the UAV formation. A multiple-objective optimisation algorithm, called the Angle-encoded Particle Swarm Optimization (theta-PSO) algorithm, is proposed to accelerate the swarm convergence with angular velocity and position being used for the location of particles. The whole formation is modelled as a virtual rigid body and controlled to maintain a desired geometric shape among the paths created while the centroid of the group follows a pre-determined trajectory. Based on the testbed of 3DR Solo drones equipped with a proprietary Mission Planner, and the Internet-of-Things (IoT) for multi-directional transmission and reception of data between the UAVs, extensive experiments have been conducted for triangular formation maintenance along a monorail bridge. The results obtained confirm the feasibility and effectiveness of the proposed approach.