This brief presents an adaptive output feedback image-based visual servoing (IBVS) law for a quadrotor unmanned aerial vehicle. The control objective is to regulate the relative 3-D position and yaw of the vehicle to a planar horizontal visual target consisting of multiple points. The control is implemented using a minimal number of commonly available low-cost on-board sensors including a strapdown inertial measurement unit and a monocular camera. The IBVS method relies on moment image features which are defined using a virtual camera. Output feedback introduces a filter to the control which removes the common requirement for linear velocity measurement. The method is adaptive and compensates for a constant force disturbance appearing the translational dynamics and parameter uncertainty in thrust constant, desired feature depth, and mass. Exponential stability of the outer loop and combined inner–outer closed-loop error dynamics is proven. Flight tests demonstrate the proposed method’s motion control performance and its ability to compensate parametric uncertainty and reject constant force disturbances.

中文翻译：

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四旋翼无人机的自适应基于输出反馈图像的视觉伺服

本简介介绍了一种适用于四旋翼无人机的自适应输出反馈基于图像的视觉伺服（IBVS）律。控制目标是将车辆的相对3D位置和偏航调整为由多个点组成的平面水平视觉目标。使用最少数量的常用低成本车载传感器（包括捷联惯性测量单元和单眼相机）来实现控制。IBVS方法依赖于使用虚拟摄像机定义的力矩图像特征。输出反馈将滤波器引入控制，从而消除了对线速度测量的通用要求。该方法是自适应的，可以补偿恒定力干扰，该干扰会出现平移动力学和推力常数，所需特征深度和质量中的参数不确定性。证明了外环的指数稳定性和内外闭环误差动力学的组合。飞行测试证明了该方法的运动控制性能及其补偿参数不确定性和消除恒定力干扰的能力。