Bayes filter implementations and show their application to real-world location-estimation tasks common in pervasive computing
暂无分享,去创建一个
[1] Gerhard Lakemeyer,et al. Exploring artificial intelligence in the new millennium , 2003 .
[2] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[3] W. Burgard,et al. Markov Localization for Mobile Robots in Dynamic Environments , 1999, J. Artif. Intell. Res..
[4] Dieter Fox,et al. Adapting the Sample Size in Particle Filters Through KLD-Sampling , 2003, Int. J. Robotics Res..
[5] Nando de Freitas,et al. Sequential Monte Carlo in Practice , 2001 .
[6] Gaetano Borriello,et al. The location stack: a layered model for location in ubiquitous computing , 2002, Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications.
[7] Stuart J. Russell,et al. Dynamic bayesian networks: representation, inference and learning , 2002 .
[8] Gaetano Borriello,et al. Location Systems for Ubiquitous Computing , 2001, Computer.
[9] Thiagalingam Kirubarajan,et al. Estimation with Applications to Tracking and Navigation , 2001 .
[10] D. Fox,et al. People Tracking with Anonymous and ID-Sensors Using Rao-Blackwellised Particle Filters , 2003, IJCAI.
[11] Yakov Bar-Shalom,et al. Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .
[12] Sebastian Thrun,et al. Robotic mapping: a survey , 2003 .
[13] John Krumm,et al. SmartMoveX on a Graph - An Inexpensive Active Badge Tracker , 2002, UbiComp.
[14] Henry A. Kautz,et al. Voronoi tracking: location estimation using sparse and noisy sensor data , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).