CONE: Collaborative Observatory for Natural Environments

这个项目是由来自德州农工大学和加州大学伯克利分校的计算机科学家和工程师，以及自然科学家和纪录片制片人共同努力的结果。目标是推进对自动化和协作系统的基本理解，这些系统将传感器、执行器和人工输入结合起来，在远程设置中观察和记录详细的自然行为。目前，对原位动物的科学研究需要在数周或数月的时间里对动物的详细行为进行警惕的观察。当动物生活在偏远和/或荒凉的地方时，对科学家来说，观察可能是一项艰巨、昂贵、危险和孤独的经历。该项目提出了一种新型的遥控/自主混合机器人“观测站”，它允许科学家小组通过互联网远程观察、记录和索引详细的动物活动。由于机器人相机、远程无线网络和分布式传感器的不断发展，这样的天文台成为可能。该项目将研究此类观测站的算法基础：新的度量、模型、数据结构和算法，这将构成一个强大的、用于协作观测的数学框架。该项目将以过去的工作为基础，扩展并正式描述利用计算几何、随机建模和优化的协作和自动观测混合模型。该项目将推进对网络机器人的基本理解，并开发有效的算法，用于将人类和传感器输入相结合的协作观察。这项工作旨在使生物科学家受益，并促进研究人员之间的合作。它将生产工作原型，并通过互联网向全世界的科学家、学生和公众开放。

This project is a collaborative effort by computer scientists and engineers from Texas A&M and UC Berkeley consulting with natural scientists and documentary filmmakers. The goal is to advance the fundamental understanding of automated and collaborative systems that combine sensors, actuators, and human input to observe and record detailed natural behavior in remote settings. Currently, scientific study of animals in situ requires vigilant observation of detailed animal behavior over weeks or months. When animals live in remote and/or inhospitable locations, observation can be an arduous, expensive, dangerous, and lonely experience for scientists. The project proposes a new class of hybrid teleoperated/autonomous robotic "observatories" that allow groups of scientists, via the internet, to remotely observe, record, and index detailed animal activity. Such observatories are made possible by emerging advances in robotic cameras, long-range wireless networking, and distributed sensors. The project will investigate the algorithmic foundations for such observatories: new metrics, models, data structures, and algorithms, that will comprise a robust, mathematical framework for collaborative observation. The project will build on past work to extend and formally characterize hybrid models of collaborative and automated observation that draw on computational geometry, stochastic modeling and optimization. The project will advance fundamental understanding of networked robotics and develop efficient algorithms for collaborative observation that combines human and sensor input. This effort is intended to benefit biological scientists and facilitate collaboration among researchers. It will produce working prototypes that will be accessible via the internet to scientists, students, and the public worldwide.