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Teleoperation of Cooperative Control of Multiple Heterogeneous Slave Unmanned Aerial Vehicles via a Single Master Subsystem for Multi-Task Multi-Target Scenarios

机译:多任务多目标场景下通过单个主子系统对多种异构奴隶无人机的协同控制进行远程操作

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This paper proposes a control method to remotely operate cooperative multiple heterogeneous slave unmanned aerial vehicles (UAVs) via a single master robot to perform different tasks on different targets in one mission. The UAV team is formed by different automated aircrafts. They are equipped with a vehicle-task-target pairing algorithm to be assigned their proper tasks and targets when moving in a leader-follower formation to track and perform assigned targets and tasks, respectively. The proposed leader-follower formation control method is modified based on a potential field algorithm to guide the UAV team or sub-team. In the UAV team, only a single leader vehicle is teleoperated by a human operator while all other follower vehicles autonomously form the formation regarding the leader movement. Therefore, the number of long distance transmission links between UAVs is reduced to minimize the possibility of occurrences of large communication delays. Besides, the vehicle-task-target pairing algorithm is derived from the proven auction algorithm for a multi-task multi-target case, which optimizes effects-based vehicle-task-target pairing based on a heuristic algorithm. The pairing method for the vehicle-task-target pairing is developed to produce a weighted attack guidance table (WAGT), which includes the benefits of assignments of robotic combinations (subteams) to tasks and targets. Therefore, the optimal robot-task-target pairs are computed based on WAGT with the heuristic algorithm. Finally, comparative simulation studies are performed to illustrate efficacy of the proposed teleoperated UAV team for multi-task multi-target scenarios to highlight the improvement of the teleoperation of the UAVs in terms of task efficiency.
机译:本文提出了一种控制方法,该方法可通过单个主机器人远程协作多个异类从属无人机,从而在一个任务中对不同目标执行不同的任务。无人机团队由不同的自动飞机组成。他们配备了车辆-任务-目标配对算法,可以在跟随领导者的队伍中移动时分别分配其适当的任务和目标,以分别跟踪和执行分配的目标和任务。基于势场算法对提出的领导者跟随编队控制方法进行了改进,以指导无人机团队或子团队。在无人机小组中,人类操作员只能对一个领导者车辆进行遥控操作,而所有其他跟随者车辆则自动形成有关领导者动作的编队。因此,减少了UAV之间的长距离传输链路的数量,以最小化发生大通信延迟的可能性。此外,车辆任务目标配对算法是从经过验证的多任务多目标案例拍卖算法中得出的,该拍卖算法基于启发式算法优化了基于效果的车辆任务目标配对。开发了用于车辆-任务-目标配对的配对方法,以生成加权攻击指导表(WAGT),其中包括将机器人组合(子团队)分配给任务和目标的好处。因此,使用启发式算法基于WAGT计算最佳机器人任务目标对。最后,进行了比较模拟研究,以说明拟议的遥控无人机团队在多任务多目标场景下的功效,以突出无人机无人机在任务效率方面的改进。

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