Dynamic Trajectory Planning for Multi-AAV Multimission Operations Using a Hybrid Strategy

Abstract

In dynamic environments characterized by terrain obstacles and spatial threats, ensuring stable execution of multiple missions (multimission) by multiple autonomous aerial vehicles (multi-AAVs) presents a significant challenge. Achieving both spatial–temporal coordination and sequential mission fulfillment remains crucial for the successful deployment of multi-AAVs in complex scenarios. This article proposes a multimission-driven hybrid strategy for multi-AAV trajectory planning. To address the inherent complexities, various models are developed, including the AAV kinematic model, relative positioning model, terrain threat model, and multimission constraint model. The proposed hybrid strategy is built on a virtual leader–follower architecture. On the one hand, an improved A* algorithm determines an optimal global path for the leader AAV that meets terminal constraints, while ensuring obstacle avoidance and minimizing path length. On the other hand, a modified navigation vector field algorithm is applied for local trajectory planning, ensuring spatial–temporal compliance and enabling a stable relative position relationship among AAVs. Compared to the three collaborative trajectory planning methods based on different frameworks, the proposed method demonstrates superior effectiveness and efficiency. Finally, the validity of the method is verified through numerical simulations and hardware-in-the-loop simulations for multimission scenarios, such as assembly, reconnaissance, and strike missions.