题目：Robotic Localization of Hostile Sensor Network
Seminar Speaker Affiliation: Texas A&M University , USA
In this talk, I will first review the three main research topics (visual navigation, robotic nature observation, and sensor network localization) in the Networked Robots Lab, Texas A&M University. Then I will focus on discussing our recent work on the localization of hostile sensor network.
We develop a localization method enabling a team of mobile robots to search for multiple unknown transient radio sources. Due to signal source anonymity, short transmission durations, and dynamic transmission patterns, robots cannot treat the radio sources as continuous radio beacons. Moreover, robots do not know the source transmission power and have limited sensing ranges. To cope with these challenges, we pair up robots and develop a sensing model using the signal strength ratio from the paired robots. We formally prove that the sensed conditional joint posterior probability of source locations for the m?robot team can be obtained by combining the pairwise joint posterior probabilities, which can be derived from signal strength ratios. Moreover, we propose a pairwise ridge walking algorithm (PRWA) to coordinate the robot pairs based on the clustering of high probability regions and the minimization of local Shannon entropy. We have implemented and validated the algorithm under hardware-driven simulation.
Dr. Dezhen Song is an Associate Professor with Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, TX, USA. Song received his Ph.D. in 2004 from University of California, Berkeley, MS and BS from Zhejiang University in 1998 and 1995, respectively. Song"s primary research area is networked robotics, visual navigation distributed sensing, computer vision, surveillance, and stochastic modeling. Dr. Song has published 1 monograph and 59 papers in selective journals and conferences. Dr. Song received the Kayamori Best Paper Award of the 2005 IEEE International Conference on Robotics and Automation (with J. Yi and S. Ding). He received NSF Faculty Early Career Development (CAREER) Award in 2007. Song co-chaired IEEE Robotics and Automation Society (RAS) Technical Committee on Networked Robots from 2007 to 2009. Song is an associate editor of IEEE Transactions on Robotics and an Associate Editor of IEEE Transactions on Automation Science and Engineering.