CAREER: Robotic BioTelemetry

职业：机器人生物遥测

• 批准号: 0643298
• 负责人: Dezhen Song
• 金额: $ 40万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643298&HistoricalAwards=false
• 关键词: CAREER; Robotic; BioTelemetry

CAREER: Robotic BioTelemetryAbstractThis project aims to develop new algorithms and systems to quantitatively measure natural habitats and animal activities via remotely controlled networked robotic cameras. Since human activity can be very disturbing to the animal under scrutiny and its colony, the project will develop new non-intrusive biotelemetry methods based on emerging advances in high-resolution networked robotic cameras and long-range wireless networking. With the potential of changing the way to study nature, the project will allow groups of scientists, via the internet, to remotely identify and measure in real-time important variables such as quantity, size, volume, speed, motion pattern, and behavior characteristics. Since objects or its collection in a natural environment are often nonlinear, non-deterministic, non-convex/concave, irregular, deformable, and time-variant / transient, the challenging problem requires new algorithm and system development. Collaborating with natural scientists, the project undertake this long term effort by building prototypes and investigating new metrics, mathematical models, algorithms, and architectures for robot biotelemetry systems in a five-year integrated research and educational project that will emphasize active robotic actuation, automation, collaboration, and optimal system design.

职业：机器人生物遥测本项目旨在开发新的算法和系统，通过远程控制的网络机器人相机定量测量自然栖息地和动物活动。由于人类活动可能会对受监视的动物及其群体造成严重干扰，该项目将根据高分辨率联网机器人相机和远程无线网络的新进展开发新的非侵入性生物遥测方法。该项目有可能改变研究自然的方式，将允许科学家通过互联网远程识别和实时测量重要变量，如数量、大小、体积、速度、运动模式和行为特征。由于自然环境中的物体或其集合通常是非线性的，非确定性的，非凸/凹的，不规则的，可变形的，和时变/瞬态的，具有挑战性的问题需要新的算法和系统开发。该项目与自然科学家合作，通过构建原型和研究机器人生物遥测系统的新指标，数学模型，算法和架构，在一个为期五年的综合研究和教育项目中进行长期努力，该项目将强调主动机器人驱动，自动化，协作和最佳系统设计。