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Kalman filter
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11	Humanoid Flexibility Deformation Can Be Efficiently Estimated Using Only Inertial Measurement Units and Contact Information Mehdi Benallegue1,2 and Florent Lamiraux1,2 Abstract— Most robots are today controlled as bein Add to Reading List Source URL: homepages.laas.fr Language: English - Date: 2014-11-13 03:18:20 Physics Engineering Mechanics Robot control Classical mechanics Rotational symmetry Aircraft instruments Theory of relativity Humanoid robot Robotics Kalman filter Inverted pendulum
12	MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Speed Sensorless State Estimation for Induction Motors: A Moving Horizon Approach Zhou, L.; Wang, Y. Add to Reading List Source URL: www.merl.com Language: English - Date: 2016-07-07 10:36:56 Electrical engineering Estimation theory Engineering Control theory Linear filters Electric motors Robot control Moving horizon estimation Vector control Kalman filter Linear regression Estimator
13	Adaptive Discriminative Generative Model and Its Applications † Ruei-Sung Lin† David Ross‡ Jongwoo Lim† Ming-Hsuan Yang∗ University of Illinois ‡ University of Toronto ∗ Honda Research Institute Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2005-01-07 15:34:20 Statistics Probability Mathematical analysis Statistical models Machine learning Markov models Linear algebra Multivariate statistics Discriminative model Kalman filter Generative model Normal distribution
14	On Predicting and Compressing Vehicular GPS Traces Sanjit Kaul and Marco Gruteser WINLAB, Rutgers University NJ, U.S.A Vinuth Rai and John Kenney Add to Reading List Source URL: www.winlab.rutgers.edu Language: English - Date: 2011-08-05 21:33:07 Mathematics Control theory Kalman filter Robot control Global Positioning System Trace Prediction Systems theory
15	Derivation of the Hierarchical EM algorithm for Dynamic Textures Antoni B. Chan Dept. of Computer Science City University of Hong Kong Emanuele Coviello Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:28 Stochastic differential equations Control theory Kalman filter Robot control Telecommunications engineering Systems theory
16	Gaussian sampling by local perturbations George Papandreou Department of Statistics University of California, Los Angeles Add to Reading List Source URL: www.stat.ucla.edu Language: English - Date: 2010-10-31 18:18:15 Statistics Statistical models Stochastic processes Linear filters Bayesian statistics Estimation theory Gibbs sampling Normal distribution Kalman filter Mixture model Bayesian network Gaussian process
17	This article was originally published in a journal published by Elsevier, and the attached copy is provided by Elsevier for the author’s benefit and for the benefit of the author’s institution, for non-commercial res Add to Reading List Source URL: ocean.mit.edu Language: English - Date: 2007-05-24 12:30:06 Control theory Mathematical analysis Academia Mathematics Mathematical optimization Numerical analysis Least squares Linear filters Kalman filter Optimal control Data assimilation Discretization
18	MATEC Web of Conferences 4 2 , ) DOI: m atecconf0 9 C Owned by the authors, published by EDP Sciences, 2016 Comparison of the SLAM algorithms: Hangar experiments Add to Reading List Source URL: www.matec-conferences.org Language: English Robotics Robot control Control theory Telecommunications engineering Extended Kalman filter Kalman filter Simultaneous localization and mapping Particle filter Unscented transform UKF Robotic mapping Robot
19	International Journal of Computer Vision The original publication is available at www.springerlink.com. Learning Articulated Structure and Motion David A. Ross · Daniel Tarlow · Richard S. Zemel Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2010-03-22 02:01:00 Computer vision Artificial intelligence Physics Dynamical systems Mechanics 3D computer graphics Robot control Computer animation Structure from motion Kinematics Bundle adjustment Kalman filter
20	Simultaneous Learning of Motion and Sensor Model Parameters for Mobile Robots Teddy N. Yap, Jr. and Christian R. Shelton Department of Computer Science and Engineering University of California, Riverside, CA 92521, USA { Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:14 Robot control Statistics Robot navigation Estimation theory Engineering Artificial intelligence Linear filters Simultaneous localization and mapping Monte Carlo methods Kalman filter Robot calibration Sensor