Abstract
In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV multi-task mission planning problem. In the first stage, the flight paths of UAVs are generated by the Dubins curve and B-spline mixed method, which are defined as “CBC)” curves, where “C” stands for circular arc and “B” stands for B-spline segment. In the second stage, the task assignment problem is solved as multi-base multi-traveling salesman problem, in which the “CBC” flight paths are used to estimate the trajectory costs. In the third stage, the flight trajectories of UAVs are generated by using Gaussian pseudospectral method (GPM). Thirdly, to improve the computational efficiency, the continuous and differential initial trajectories are generated based on the “CBC” flight paths. Finally, numerical simulations are presented to demonstrate the proposed approach, the designed initial solution search algorithm is compared with existing methods. These results indicate that the proposed hierarchical mission planning method can produce satisfactory mission planning results efficiently.
Highlights
UAVs have seen decades of successful deployment in military operations
The task assignment problem is modeled as a multi-base multi-traveling salesman problem (MBMTSP) 16
This paper proposes mixing the B-spline and Dubins curves together to take advantage of their characteristics
Summary
UAVs have seen decades of successful deployment in military operations. These military UAVs are traditionally large and expensive. Many algorithms have been proposed to solve the trajectory planning problem of multiple UAVs. Bai Li et al propose the centralized motion planning method based on the optimization algorithm, which generates satisfying planning results within sufficient time [13]. Gu Xueqiang et al propose a distributed receding horizon planning method [15], without considering the task assignment problem Intelligent algorithms such as the genetic algorithm have been proposed to solve the multi-UAV trajectory planning problem [16,17]. The Dubins curve and B-spline curve are mixed to generate flight paths of UAVs, with respect to the dynamic constraints and obstacle avoidance requirements This gives a reasonable estimation of the cost of each flight trajectory.
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