Chapter 11 Sensors and Information Spaces
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[1] H. W. Kuhn,et al. 11. Extensive Games and the Problem of Information , 1953 .
[2] Y. Ho,et al. Team decision theory and information structures in optimal control problems: Part II , 1971, CDC 1971.
[3] Jeffrey D. Ullman,et al. Introduction to Automata Theory, Languages and Computation , 1979 .
[4] T. Başar,et al. Dynamic Noncooperative Game Theory , 1982 .
[5] Gerald B. Folland,et al. Real Analysis: Modern Techniques and Their Applications , 1984 .
[6] Russell H. Taylor,et al. Automatic Synthesis of Fine-Motion Strategies for Robots , 1984 .
[7] P. Abbeel,et al. Kalman filtering , 2020, IEEE Control Systems Magazine.
[8] R. Bertram,et al. Stochastic Systems , 2008, Control Theory for Physicists.
[9] Matthew T. Mason,et al. An exploration of sensorless manipulation , 1986, IEEE J. Robotics Autom..
[10] Lyle A. McGeoch,et al. Competitive algorithms for on-line problems , 1988, STOC '88.
[11] Eitan M. Gurari,et al. Introduction to the theory of computation , 1989 .
[12] Kenneth Y. Goldberg,et al. Bayesian grasping , 1990, Proceedings., IEEE International Conference on Robotics and Automation.
[13] Ken Goldberg,et al. Stochastic plans for robotic manipulation , 1991 .
[14] Bruce Randall Donald,et al. Sensor interpretation and task-directed planning using perceptual equivalence classes , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.
[15] Steven M. LaValle,et al. An objective-based stochastic framework for manipulation planning , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).
[16] Robert F. Stengel,et al. Optimal Control and Estimation , 1994 .
[17] Chi-Tsong Chen,et al. Linear System Theory and Design , 1995 .
[18] Jérôme Barraquand,et al. Motion planning with uncertainty: the information space approach , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.
[19] Bruce Randall Donald,et al. On Information Invariants in Robotics , 1995, Artif. Intell..
[20] G. Kitagawa. Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models , 1996 .
[21] Steven M. LaValle,et al. An Objective-Based Framework for Motion Planning under Sensing and Control Uncertainties , 1998, Int. J. Robotics Res..
[22] H. Kushner. Numerical Methods for Stochastic Control Problems in Continuous Time , 2000 .
[23] Wolfram Burgard,et al. Particle Filters for Mobile Robot Localization , 2001, Sequential Monte Carlo Methods in Practice.
[24] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[25] T. Başar,et al. A New Approach to Linear Filtering and Prediction Problems , 2001 .
[26] Timothy J. Robinson,et al. Sequential Monte Carlo Methods in Practice , 2003 .
[27] Michael A. Erdmann,et al. Randomization for robot tasks: Using dynamic programming in the space of knowledge states , 1993, Algorithmica.
[28] Kristine L. Bell,et al. A Tutorial on Particle Filters for Online Nonlinear/NonGaussian Bayesian Tracking , 2007 .
[29] Nahum Shimkin,et al. Nonlinear Control Systems , 2008 .