Swarm Intelligence in Collision-free Formation Control for Multi-UAV Systems with 3D Obstacle Avoidance Maneuvers

TL;DR

This paper introduces a nature-inspired, collision-free control framework for multi-UAV systems in 3D environments, enabling obstacle avoidance and formation control inspired by animal behaviors, validated through simulations with obstacles.

Contribution

It presents a novel, centralized and distributed control framework inspired by animal behavior, extended to 3D space for multi-UAV obstacle avoidance and formation control.

Findings

Framework successfully avoids static and dynamic obstacles in 2D and 3D scenarios.

Validates effectiveness in urban-like environments with buildings and obstacles.

Demonstrates robust formation control with collision avoidance capabilities.

Abstract

Recent advances in multi-agent systems manipulation have demonstrated a rising demand for the implementation of multi-UAV systems in urban areas which are always subjected to the presence of static and dynamic obstacles. The focus of the presented research is on the introduction of a nature-inspired collision-free control for a multi-UAV system considering obstacle avoidance maneuvers. Inspired by the collective behavior of tilapia fish and pigeon, the presented framework in this study uses a centralized controller for the optimal formation control/recovery, which is defined by probabilistic Lloyd's algorithm, while it uses a distributed controller for the intervehicle collision and obstacle avoidance. Further, the presented framework has been extended to the 3D space with 3D maneuvers. Finally, the presented framework has been applied to a multi-UAV system in 2D and 3D scenarios, and obtained results demonstrated the validity of the presented method in the presence of buildings and different types of obstacles.