CONE: Collaborative Observatory for Natural Environments

CONE：自然环境合作观测站

• 批准号: 0535218
• 负责人: Ken Goldberg
• 金额: --
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0535218&HistoricalAwards=false
• 关键词: CONE; Collaborative; Observatory; Natural; Environments

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.

这个项目是由德克萨斯州A&A；M和加州大学伯克利分校的计算机科学家和工程师与自然科学家和纪录片制片人合作完成的。其目标是促进对自动化和协作系统的基本理解，该系统将传感器、执行器和人工输入结合在一起，以观察和记录远程环境中的详细自然行为。目前，对现场动物的科学研究需要在几周或几个月内对动物的详细行为进行警惕的观察。当动物生活在偏远和/或不适宜居住的地方时，对科学家来说，观察可能是一种艰巨、昂贵、危险和孤独的经历。该项目提出了一种新的混合远程操作/自主机器人“观察站”，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。机器人摄像机、远程无线网络和分布式传感器的不断进步使这样的观测站成为可能。该项目将调查这类观测站的算法基础：新的指标、模型、数据结构和算法，它们将构成一个强大的、用于协作观测的数学框架。该项目将在过去工作的基础上，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察的混合模型。该项目将促进对联网机器人的基本理解，并开发结合人类和传感器输入的高效协作观察算法。这一努力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，全世界的科学家、学生和公众都可以通过互联网访问这些原型。