无人船与人工协作监测水体杂草，提升生态管理效率
Human-Robot Collaboration System Setup for Weed Harvesting Scenarios in Aquatic Lakes
- 无人船用多波束声呐探测水下杂草分布
- 初步实验显示对水体杂草定位准确率高
- 适合水域生态监测与智能农业场景
人造水体（AWBs）为人工系统，需持续监控其人工生物过程。为有效管理生态系统，须定期维护。无人水面艇（USV）可与船员协同工作，识别特定位置。本文探讨了水体杂草收割场景，展示了人机协作的实现方式，并给出了初步结果。USV主要利用多波束声呐（SONAR）进行水下杂草监测，在该场景中表现良好。
原文摘要 · Abstract (English)
Artificial Water Bodies (AWBs) are human-made and require continuous monitoring due to their artificial biological processes. These systems necessitate regular maintenance to manage their ecosystems effectively. Unmanned Surface Vehicle (USV) offers a collaborative approach for monitoring these environments, working alongside human operators such as boat skippers to identify specific locations. This paper discusses a weed harvesting scenario, demonstrating how human-robot collaboration can be achieved, supported by preliminary results. The USV mainly utilises multibeam SOund NAvigation and Ranging (SONAR) for underwater weed monitoring, showing promising outcomes in these scenarios.
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