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ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 6 days ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
ICRA
1999
IEEE
126views Robotics» more  ICRA 1999»
13 years 10 months ago
Monte Carlo Localization for Mobile Robots
Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilisticlocalization algorithms known as Monte...
Frank Dellaert, Dieter Fox, Wolfram Burgard, Sebas...
AUTOMATICA
2011
13 years 24 days ago
A frequentist approach to mapping under uncertainty
An asynchronous stochastic approximation based (Frequentist) approach is proposed for mapping using noisy mobile sensors under two different scenarios: 1) perfectly known sensor ...
Suman Chakravorty, R. Saha
ICRA
1998
IEEE
117views Robotics» more  ICRA 1998»
13 years 10 months ago
Integrating Dependent Sensory Data
In sensory data fusion and integration consideration, sensor independence is a common assumption. In this paper, we demonstrated the impact of including dependent information in s...
Albert C. S. Chung, Helen C. Shen
ICIP
2009
IEEE
14 years 6 months ago
Efficient Multivariate Skellam Shrinkage For Denoising Photon-limited Image Data: An Empirical Bayes Approach
In this article we address the issue of denoising photon-limited image data by deriving new and efficient multivariate Bayesian estimators that approximate the conditional expecta...