首 页 | 研究所概况 | 科研队伍 | 新闻动态 | 科研状况 | 学术交流 | 成果转化 | 招生工作 
学术报告
2013年春季先进机器人与MEMS技术系列学术讲座(56)
添加日期:2013-07-03 作者:周璐老师 来源:

南开大学机器人与信息自动化研究所
Institute of Robotics and Automatic Information System
2013年春季先进机器人与MEMS技术系列学术讲座
Seminar Series:Advanced Robotics & MEMS

题目:Collaborative Observation of Natural Environments

报告人:宋德臻 博士

单位:Texas A\&M University, College Station, TX, USA

时间:2013年7月4日(周四)10:00-11:00

地点:伯苓楼一楼机器人所资料室

Abstract: 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. Emerging advances in robot cameras, long-range wireless networking, and distributed sensors make feasible a new class of portable robotic observatories that can allow groups of scientists, via the internet, to remotely observe, record, and index detailed animal activity. As a shorthand for such an instrument, we propose the acronym CONE: Collaborative Observatory for Natural Environments.
One challenge is to develop a mathematical framework for collaborative observation. Collaborative observation includes (1) collaboration between humans of different backgrounds, skill sets, and authority/permission levels, (2) collaboration between humans and automated agents whose behavior arises from sensor inputs and/or computation, and (3) automatic detection of species and activities.
In this talk, I will summarize our eight-year development of algorithms, CONE systems, lessons learned, and results of field experiments.

Bio: Dezhen Song received the B.S. and M.S. degrees from Zhejiang University, Hangzhou, China, in 1995 and 1998, respectively, and the Ph.D. degree from the University of California, Berkeley, in 2004. He is currently an Associate Professor with the Department of Computer Science and Engineering, Texas A\&M University, College Station, TX. His primary research interests include networked robotics, distributed sensing, computer vision, surveillance, and stochastic modeling. Dr. Song received the Kayamori Best Paper Award at the 2005 IEEE International Conference on Robotics and Automation (with J. Yi and S. Ding). He received the National Science Foundation Faculty Early Career Development (CAREER) Award in 2007. He co-chaired IEEE Robotics and Automation Society Technical Committee on Networked Robots from 2007 to 2009. From 2008 to 2012, he was an Associate Editor of the IEEE TRANSACTIONS ON ROBOTICS. He is an Associate Editor of the IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING.

本次讲座由南开大学研究生创新计划资助