NRI: An Ecologically Curious Robot for Monitoring Coral Reef Biodiversity

这笔赠款将资助能够监测和管理珊瑚礁的研究，珊瑚礁是关键的生物多样性热点，为自给自足和商业捕鱼、旅游业以及海岸保护提供直接经济利益，从而促进科学进步，促进国家繁荣和福祉。世界各地的珊瑚礁正受到人为干扰的威胁，包括气候变化和相关的海洋酸化。需要新的工具来扩大对珊瑚礁的监测，以了解珊瑚礁生态系统，快速评估生物多样性，并衡量干预措施的效果。这个跨学科的项目将通过创建一个自主机器人系统来满足这一需求，该系统可以在复杂的生态系统中导航，并智能地对其环境进行采样，以评估当地的生物多样性和生态系统健康。虽然该项目将侧重于监测珊瑚礁的水下系统，但估算生物多样性的方法直接适用于监测其他复杂和受威胁的生态系统，如雨林，或在其他偏远生境中寻找和绘制生物多样性地图。与计划进行实地考察的美属维尔京群岛为少数族裔服务的机构建立伙伴关系，以及参与伍兹霍尔学院暑期学生和少数族裔奖学金计划，将有助于扩大目前代表性不足群体和为他们提供服务的机构的学生对STEM的参与。这项研究旨在为水下自主机器人技术的集成做出基础性贡献，该机器人能够利用从声学和视觉测量获得的高维信息在复杂环境中进行智能路径规划、决策和运动。它将通过开发一种新型的海底跳跃机器人来实现这一结果，该机器人能够在观察环境的长时间静止周期之间交替，同时将对动物生命的干扰降至最低，并保存其能量收支，从一个着陆点到下一个着陆点进行短暂的游泳活动。该项目将开发一种新的解决方案，以解决信息性路径规划问题，特别是与不同类型的栖息地、植物和动物的观察相关的分类数据。它将把这个问题建模为一个部分可观测的马尔可夫决策过程，并将探索新的方法，根据深度学习技术和贝叶斯非参数使环境的估计生物多样性和真实生物多样性之间的误差来计算预期奖励推出。实地考察将包括验证用于栖息地分类的视觉珊瑚礁调查算法，收集用于机器学习算法的训练数据，以及测试用于定位生物多样性热点和长任务持续时间的路径规划算法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This grant will fund research that enables monitoring and management of coral reefs, which are critical biodiversity hotspots that provide direct economic benefits for subsistence and commercial fishing, tourism, and through coastal protection, thereby promoting the progress of science and advancing the national prosperity and welfare. Coral reefs worldwide are under threat from anthropogenic disturbances including climate change and associated ocean acidification. New tools are needed to scale up monitoring of coral reefs to understand reef ecosystems, rapidly assess biodiversity, and measure the efficacy of interventions. This interdisciplinary project will address this need by creating an autonomous robotic system that can navigate a complex ecosystem and intelligently sample its environment to estimate local biodiversity and ecosystem health. While the project will focus on an underwater system for monitoring coral reefs, the approach for estimating biodiversity is directly applicable to monitoring of other complex and threatened ecosystems such as rainforests, or for seeking out and mapping biodiversity in other remote habitats. A partnership with a minority-serving institution in the US Virgin Islands, the site for planned field expeditions, as well as participation in the Woods Hole Institute Summer Student and Minority Fellowship program, will help broaden participation in STEM of students from currently underrepresented groups and the institutions that serve them. This research aims to make fundamental contributions to the integration of robotic technologies in an underwater autonomous vehicle that is capable of intelligent path planning, decision-making, and locomotion in a complex environment using high-dimensional information gained from acoustic and visual measurements. It will achieve this outcome by developing a novel seafloor hopping robot that is able to alternate between long stationary periods of observing its environment, while minimizing disturbances to animal life and conserving its energy budget, with short bursts of swimming activity from one landing spot to the next. The project will develop a novel solution to the informative path planning problem particular to categorical data associated with observations of different types of habitat, plants, and animals. It will model this problem as a partially observable Markov decision process and will explore new approaches for computing expected reward rollouts in terms of the error between the estimated and true biodiversity of the environment, enabled by deep learning techniques and Bayesian nonparametrics. Field expeditions will include validation of visual reef survey algorithms for habitat classification, collection of training data for machine learning algorithms, and tests of the path planning algorithm for locating biodiversity hotspots and long mission durations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.