Autonomous Vision-Guided Object Collection From Water Surfaces With a Customized Multirotor

Abstract

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%.