论文标题
进行大规模的自主监测和感知水下污染物
Toward Large-Scale Autonomous Monitoring and Sensing of Underwater Pollutants
论文作者
论文摘要
海洋污染是全球范围内日益严重的关注,影响了海洋生态系统,人类健康,气候变化和天气模式的健康。为了减少水下污染,至关重要的是,无法选择适当的对策和清洁措施的准确信息。目前,由于现有的监测解决方案高度艰辛或昂贵,仅限于特定污染物,并且空间和时间分辨率有限,因此很难获取此类信息。在本文中,我们介绍了大规模自动海洋污染监测的研究愿景,该研究使用了使用协调的自动水下车辆(AUV)来监控海洋污染物的程度和特征。我们重点介绍了关键要求和参考技术,以建立研究路线图,以实现这一愿景。我们还解决了愿景的可行性,进行了受控的实验,以解决污染物和协作水下处理的分类,这对我们的愿景面临两个关键的研究挑战。
Marine pollution is a growing worldwide concern, affecting health of marine ecosystems, human health, climate change, and weather patterns. To reduce underwater pollution, it is critical to have access to accurate information about the extent of marine pollutants as otherwise appropriate countermeasures and cleaning measures cannot be chosen. Currently such information is difficult to acquire as existing monitoring solutions are highly laborious or costly, limited to specific pollutants, and have limited spatial and temporal resolution. In this article, we present a research vision of large-scale autonomous marine pollution monitoring that uses coordinated groups of autonomous underwater vehicles (AUV)s to monitor extent and characteristics of marine pollutants. We highlight key requirements and reference technologies to establish a research roadmap for realizing this vision. We also address the feasibility of our vision, carrying out controlled experiments that address classification of pollutants and collaborative underwater processing, two key research challenges for our vision.