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MPC controlled multirotor with suspended slung Load: System architecture and visual load detection

机译:MPC控制的多转子悬吊负载:系统架构和视觉负载检测

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There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (¿¿¿5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.
机译:人们越来越希望将无人机用于从环境遥感到建筑和包裹运输的负载运输。主要挑战之一是精确控制负载位置和轨迹。本文仅通过视觉反馈来确定负载位置,从而对实际的飞行试验进行评估,以控制带有悬挂的悬挂负载的自主多旋翼。该方法使用车载摄像机来利用常见的视觉标记检测算法来稳健地检测负载位置。使用车载处理器计算负载位置,然后通过无线网络将其传输到集成了MATLAB / SIMULINK和机器人操作系统(ROS)和模型预测控制器(MPC)的地面站,以控制负载和无人机。为了评估系统性能,将视觉检测系统在实际飞行中确定的负载位置与运动跟踪系统接收的数据进行比较。多旋翼位置跟踪性能也可以通过使用完美的载荷位置数据和仅从视觉系统获得的数据进行飞行试验来进行分析。结果显示仅使用视觉系统即可非常准确地估计负载位置(偏移5%),并表明此任务不需要外部运动跟踪系统。

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