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Cooperative control of multiple unmanned aerial systems for heavy duty carrying

机译:多种用于重型载运的无人机系统的协同控制

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The idea of cooperative carrying using a team of unmanned aerial vehicles (UAVs) has been viewed as a widely applicable and deployable use of unmanned multi-agent systems, yet there are very few working systems that can successfully perform such tasks due to the complexities involved. One of the primary challenges is the limited control authority of the cooperative team due to the scale of the individual agents being necessarily much smaller than the load. Here, we propose a general method that can be used to optimise the control authority of a UAV team in the case where the agents are rigidly mounted to the payload. Firstly, a tilt angle for each UAV relative to the payload is introduced to improve the yaw control of the system, as a large wide payload will invariably have a large moment of inertia in the yaw axis. The positional placement of the UAVs and the value of the tilt angle that maximises control authority was then found using an evolutionary algorithm. The optimised solution based on a case study task involves using four UAVs placed at the corner of a square payload with an inward tilt, which can be effectively controlled as a single large quadrotor. Testing results show that the full system carrying the payload can execute given trajectories autonomously with high accuracy and precision, effectively performing the task of cooperative carrying. The proposed system was successfully demonstrated at the 2017 International Micro Air Vehicles Competition.
机译:使用无人飞行器(UAV)团队进行协作运载的想法已被认为是无人驾驶多智能体系统的广泛适用和可部署使用,但是由于涉及的复杂性,很少有能够成功执行此类任务的工作系统。主要挑战之一是合作团队的控制权有限,这是因为单个代理的规模必然比负载小得多。在这里,我们提出了一种通用方法,在特工被牢固地安装到有效载荷的情况下,可用于优化无人机团队的控制权限。首先,引入每个无人机相对于有效载荷的倾斜角,以改善系统的偏航控制,因为较大的较宽的有效载荷将始终在偏航轴上具有较大的惯性矩。然后使用进化算法找到无人机的位置位置和使控制权最大化的倾斜角的值。基于案例研究任务的优化解决方案涉及使用四个无人机,它们以向内倾斜的方式放置在方形有效载荷的一角,可以将其作为一个大型四旋翼有效控制。测试结果表明,运载有效载荷的整个系统可以高精度,自主地执行给定的轨迹,有效地完成了协同运载的任务。拟议的系统已在2017年国际微型飞行器竞赛中成功展示。

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