Novel Pigeon-inspired 3D Obstacle Detection and Avoidance Maneuver for Multi-UAV Systems

TL;DR

This paper introduces a novel, nature-inspired 3D obstacle detection and avoidance framework for multi-UAV systems, combining centralized guidance with distributed control, validated in dynamic environments with static and moving obstacles.

Contribution

It presents a new 3D collision avoidance method inspired by bird and fish behavior, integrating probabilistic algorithms with semi-distributed control for multi-UAV systems.

Findings

Effective obstacle avoidance in 2D and 3D scenarios

Validates approach in dynamic environments with moving obstacles

Demonstrates improved formation control and safety

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. Inspired by the collective behavior of tilapia fish and pigeons, the focus of the presented research is on the introduction of a nature-inspired collision-free formation control for a multi-UAV system, considering the obstacle avoidance maneuvers. The developed framework in this study utilizes a semi-distributed control approach, in which, based on a probabilistic Lloyd's algorithm, a centralized guidance algorithm works for optimal positioning of the UAVs, while a distributed control approach has been used for the intervehicle collision and obstacle avoidance. Further, the presented framework has been extended to the 3D space with a novel definition of 3D maneuvers. Finally, the presented framework has been applied to multi-UAV systems in 2D and 3D scenarios, and the obtained results demonstrated the validity of the presented method in dynamic environments with stationary and moving obstacles.