Belief space planning assuming maximum likelihood observations Robert Platt Jr., Russ Tedrake, Leslie Kaelbling, Tomas Lozano-Perez Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Techn

First Page		Document Content
Date: 2011-02-22 11:30:08 Stochastic control Optimal control Estimation theory Robot control Kalman filter Partially observable Markov decision process Linear-quadratic-Gaussian control Algebraic Riccati equation Maximum likelihood Control theory Statistics Systems theory		Belief space planning assuming maximum likelihood observations Robert Platt Jr., Russ Tedrake, Leslie Kaelbling, Tomas Lozano-Perez Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Techn Add to Reading List Source URL: groups.csail.mit.edu Download Document from Source Website File Size: 172,62 KB Share Document on Facebook

	Quantitative Verification and Strategy Synthesis for Stochastic Games M´aria Svoreˇnov´a and Marta Kwiatkowska Abstract— Design and control of computer systems that operate in uncertain, competitive or adversarial, DocID: 1xVYM - View Document
	Quantitative Verification and Strategy Synthesis for Stochastic Games M´aria Svoreˇnov´a and Marta Kwiatkowska Abstract— Design and control of computer systems that operate in uncertain, competitive or adversarial, DocID: 1xUuJ - View Document
	2017 American Control Conference Sheraton Seattle Hotel May 24–26, 2017, Seattle, USA Stochastic Predictive Freeway Ramp Metering from Signal Temporal Logic Specifications DocID: 1vrV2 - View Document
	EE363 WinterLecture 10 Linear Quadratic Stochastic Control with DocID: 1vrTL - View Document
	EE266 and MS&E251: Introduction About the course Optimization Dynamical systems Stochastic control DocID: 1vkoK - View Document