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AAAI
2000
13 years 8 months ago
Monte Carlo Localization with Mixture Proposal Distribution
Monte Carlo localization (MCL) is a Bayesian algorithm for mobile robot localization based on particle filters, which has enjoyed great practical success. This paper points out a ...
Sebastian Thrun, Dieter Fox, Wolfram Burgard
CORR
2002
Springer
113views Education» more  CORR 2002»
13 years 7 months ago
Robust Global Localization Using Clustered Particle Filtering
Global mobile robot localization is the problem of determining a robot's pose in an environment, using sensor data, when the starting position is unknown. A family of probabi...
Javier Nicolás Sánchez, Adam Milstei...
CVPR
2009
IEEE
15 years 2 months ago
Memory-based particle filter for face pose tracking robust under complex dynamics
A novel particle filter, the Memory-based Particle Filter (M-PF), is proposed that can visually track moving objects that have complex dynamics. We aim to realize robustness aga...
Dan Mikami (NTT), Kazuhiro Otsuka (NTT), Junji YAM...
CORR
2007
Springer
94views Education» more  CORR 2007»
13 years 7 months ago
Universal Quantile Estimation with Feedback in the Communication-Constrained Setting
Abstract— We consider the following problem of decentralized statistical inference: given i.i.d. samples from an unknown distribution, estimate an arbitrary quantile subject to l...
Ram Rajagopal, Martin J. Wainwright
CORR
2007
Springer
144views Education» more  CORR 2007»
13 years 7 months ago
Distributing the Kalman Filter for Large-Scale Systems
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
Usman A. Khan, José M. F. Moura