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Details

Autor(en) / Beteiligte
Titel
Evaluation of the Utility and Performance of an Autonomous Surface Vehicle for Mobile Monitoring of Waterborne Biochemical Agents
Ist Teil von
  • OCEANS 2021: San Diego – Porto, 2021, p.1-10
Ort / Verlag
MTS
Erscheinungsjahr
2021
Quelle
IEEE Xplore
Beschreibungen/Notizen
  • The need for real-time monitoring and management of water quality in inland and coastal marine environments is increasingly significant due to increases in land utilization which can negatively impact aquatic ecosystems from surface water runoff. Conventional water quality monitoring methodologies are laborious and expensive, requiring in situ monitoring stations and/or specialized manned vessel sampling missions at fixed locations and resultant laboratory analysis of water samples. These conventional methods are limited in their ability to gather high resolution spatiotemporal data. Multi-purpose autonomous surface vehicles (ASVs) provide a powered platform for sensors/instrumentation and serve as mobile sampling stations that enhance spatial and temporal data gathering capabilities. Solar powered ASVs provide long endurance continuous operations capabilities. However, commercially available solar powered ASVs are limited, and ASV autopilot navigational accuracy is affected by environmental forces (wind, current, and waves) that can alter trajectories of planned paths and negatively affect spatio-temporal resolution of water quality data. This study demonstrated the ability of a commercially available solar powered ASV equipped with a multi-sensor payload to operate autonomously to accurately and repeatedly maintain established AB line transects under varying environmental conditions, where lateral deviation from a planned linear route was measured and expressed as cross-track error (XTE). Mean XTE did not exceed 2.39 m. This work provides a conceptual framework for development of spatial and temporal resolution limitations of ASVs for real-time monitoring campaigns and future development of obstacle avoidance and adaptive sampling technologies.
Sprache
Englisch
Identifikatoren
DOI: 10.23919/OCEANS44145.2021.9705834
Titel-ID: cdi_ieee_primary_9705834

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