Fuzzy Logic-Based Path Planning for UAV Swarms with Molecular-Inspired Movement

This study, based on a realistic quadrotor UAV model, proposes an intelligent path planning method for UAV swarms by integrating fuzzy logic and molecular mechanics perspectives. UAVs are modeled as atoms in a molecule, where their internal clustering mechanisms correspond to intramolecular forces, and their interactions with the environment correspond to intermolecular forces. The intramolecular forces include attraction and repulsion between UAVs: attraction ensures stable formations within the communication range, while repulsion prevents collisions within the safety distance. Intermolecular forces simulate the interactions between UAVs and targets or obstacles, where the attraction to a target is analogous to induction forces for long-range guidance, and the repulsion from obstacles is similar to the Pauli exclusion principle for short-range collision avoidance. Utilizing the dynamics of a realistic quadrotor UAV model, this method achieves a dynamic balance between attraction and repulsion, enabling the swarm to maintain coordinated stability while adapting its path in complex environments. The study demonstrates the effectiveness of the on-the-fly path generation strategy, offering theoretical support and practical potential for intelligent control in multi-UAV systems.