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Main Authors: Elsayed, Ahmed H., Manss, Christoph, El-Mihoub, Tarek A., Lejman, Andrej, Stahl, Frederic
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.06266
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author Elsayed, Ahmed H.
Manss, Christoph
El-Mihoub, Tarek A.
Lejman, Andrej
Stahl, Frederic
author_facet Elsayed, Ahmed H.
Manss, Christoph
El-Mihoub, Tarek A.
Lejman, Andrej
Stahl, Frederic
contents Artificial Water Bodies (AWBs) are human-made systems that require continuous monitoring due to their artificial biological processes. These systems demand regular maintenance to manage their ecosystems effectively. As a result of these artificial conditions, underwater vegetation can grow rapidly and must be harvested to preserve the ecological balance. This paper proposes a two-step approach to support targeted weed harvesting for the maintenance of artificial lakes. The first step is the initial detection of Submerged Aquatic Vegetation (SAV), also referred to in this paper as areas of interest, is performed using satellite-derived indices, specifically the Aquatic Plants and Algae (APA) index, which highlights submerged vegetation in water bodies. Subsequently, an Unmanned Surface Vehicle (USV) equipped with multibeam SOund NAvigation and Ranging (SONAR) performs high-resolution bathymetric mapping to locate and quantify aquatic vegetation precisely. This two-stage approach offers an effective human-robot collaboration, where satellite data guides the USV missions and boat skippers leverage detailed SONAR maps for targeted harvesting. This setup narrows the search space and reduces manual workload from human operators, making the harvesting process less labour-intensive for operators. Preliminary results demonstrate the feasibility of integrating satellite imagery and underwater acoustic sensing to improve vegetation management in artificial lakes.
format Preprint
id arxiv_https___arxiv_org_abs_2603_06266
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Towards Robotic Lake Maintenance: Integrating SONAR and Satellite Data to Assist Human Operators
Elsayed, Ahmed H.
Manss, Christoph
El-Mihoub, Tarek A.
Lejman, Andrej
Stahl, Frederic
Robotics
Artificial Water Bodies (AWBs) are human-made systems that require continuous monitoring due to their artificial biological processes. These systems demand regular maintenance to manage their ecosystems effectively. As a result of these artificial conditions, underwater vegetation can grow rapidly and must be harvested to preserve the ecological balance. This paper proposes a two-step approach to support targeted weed harvesting for the maintenance of artificial lakes. The first step is the initial detection of Submerged Aquatic Vegetation (SAV), also referred to in this paper as areas of interest, is performed using satellite-derived indices, specifically the Aquatic Plants and Algae (APA) index, which highlights submerged vegetation in water bodies. Subsequently, an Unmanned Surface Vehicle (USV) equipped with multibeam SOund NAvigation and Ranging (SONAR) performs high-resolution bathymetric mapping to locate and quantify aquatic vegetation precisely. This two-stage approach offers an effective human-robot collaboration, where satellite data guides the USV missions and boat skippers leverage detailed SONAR maps for targeted harvesting. This setup narrows the search space and reduces manual workload from human operators, making the harvesting process less labour-intensive for operators. Preliminary results demonstrate the feasibility of integrating satellite imagery and underwater acoustic sensing to improve vegetation management in artificial lakes.
title Towards Robotic Lake Maintenance: Integrating SONAR and Satellite Data to Assist Human Operators
topic Robotics
url https://arxiv.org/abs/2603.06266