Coral reefs are under increasing threat from the impacts of climate change. Whilst current restoration approaches are effective, they require significant human involvement and equipment, and have limited deployment scale. Harvesting wild coral spawn from mass spawning events, rearing them to the larval stage and releasing the larvae onto degraded reefs is an emerging solution for reef restoration known as coral reseeding. This paper presents a reconfigurable autonomous surface vehicle system that can eliminate risky diving, cover greater areas with coral larvae, has a sensory suite for additional data measurement, and requires minimal non-technical expert training. A key feature is an on-board real-time benthic substrate classification model that predicts when to release larvae to increase settlement rate and ultimately, survivability. The presented robot design is reconfigurable, light weight, scalable, and easy to transport. Results from restoration deployments at Lizard Island demonstrate improved coral larvae release onto appropriate coral substrate, while also achieving 21.8 times more area coverage compared to manual methods.
翻译:珊瑚礁正日益受到气候变化影响的威胁。虽然目前的恢复方法是有效的,但它们需要大量的人类参与和设备,而且部署规模有限。从大规模产卵事件中捕获野生珊瑚产卵,将其培养到幼虫阶段,并将幼虫释放到退化的珊瑚礁,这是珊瑚礁恢复的新兴解决办法,称为珊瑚再播种。本文件介绍了可重新配置的自主地表水车辆系统,该系统可以消除危险的潜水,覆盖更多的珊瑚幼虫地区,拥有一套用于额外数据测量的感官套件,并且需要最低限度的非技术专家培训。一个关键特征是,在船上实时海底海底基底分类模型,预测何时释放幼虫,以提高定居率并最终存活率。提出的机器人设计是可重新配置的、轻重的、可伸缩的和易于迁移的。在利查德岛的恢复部署结果显示珊瑚幼虫被释放到适当的珊瑚子下层的情况有所改善,同时与人工方法相比,覆盖面积增加了21.8倍。