This article presents a multirotor system with an integrated net mechanism for autonomous object detection and collection from water surfaces utilizing only onboard sensors. The task of object collection on water surfaces is challenging due to the following reasons: 1) propeller outwash alters the object's dynamics; 2) unpredictable current flows, 3) extreme reflection and glare off water surfaces affect the object detection; and 4) noisy height measurements over water surface. A two-phase object-detection algorithm is developed with a linearized polarization filter and specularity removal algorithm to eliminate reflections and an edge-based contour detector for detection of objects on water surface. Subsequently, a boundary layer sliding-mode control is implemented to ensure the system is robust to modeling uncertainties. A dynamic sliding surface is designed based on constrained linear model predictive control. The efficacy of the proposed collection system is validated by multiple outdoor tests. Multiple objects of different shapes and sizes are collected with an overall success rate of 91.6%.

中文翻译：

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使用定制多旋翼自主视觉引导水面物体收集


本文介绍了一种具有集成网络机制的多旋翼系统，可仅利用机载传感器从水面进行自主物体检测和收集。由于以下原因，水面上的物体收集任务具有挑战性：1）螺旋桨冲刷改变了物体的动力学； 2）不可预测的水流，3）水面的极端反射和眩光影响物体检测； 4) 水面上的噪声高度测量。开发了一种两阶段物体检测算法，采用线性偏振滤波器和镜面去除算法来消除反射，并使用基于边缘的轮廓检测器来检测水面上的物体。随后，实施边界层滑模控制以确保系统对建模不确定性具有鲁棒性。基于约束线性模型预测控制设计动态滑动面。所提出的收集系统的功效通过多次户外测试得到验证。收集多个不同形状和大小的物体，总体成功率为 91.6%。