Dynamic real-time multi-UAV cooperative mission planning method under multiple constraints

TL;DR

This paper introduces a dynamic, real-time multi-UAV mission planning algorithm that effectively balances path optimality and computational speed, enhancing adaptability and responsiveness in complex scenarios.

Contribution

It presents a novel distributed formation-based planning method using Dubins paths with acceleration techniques for real-time, coupled task assignment and path planning.

Findings

Achieves only 9.57% longer paths compared to optimal solutions.

Speeds up planning by 4-5 orders of magnitude over simulated annealing.

Performs single mission planning in approximately 0.0003 seconds.

Abstract

As UAV popularity soars, so does the mission planning associated with it. The classical approaches suffer from the triple problems of decoupled of task assignment and path planning, poor real-time performance and limited adaptability. Aiming at these challenges, this paper proposes a dynamic real-time multi-UAV collaborative mission planning algorithm based on Dubins paths under a distributed formation structure. Dubins path with multiple advantages bridges the gap between task assignment and path planning, leading to a coupled solution for mission planning. Then, a series of acceleration techniques, task clustering preprocessing, highly efficient distance cost functions, low-complexity and less iterative task allocation strategies, are employed to guarantee the real-time performance of the algorithms. To cope with different emergencies and their simultaneous extremes, real-time planning of emerging tasks and mission replanning due to the reduction of available UAVs are appropriately handled. Finally, the developed algorithm is comprehensively exemplified and studied through simulations, highlighting that the proposed method only sacrifices 9.57% of the path length, while achieving a speed improvement of 4-5 orders of magnitude over the simulated annealing method, with a single mission planning of about 0.0003s.