39 search results - page 4 / 8 » Bayesian Estimation and Kalman Filtering: A Unified Framewor... |
ICRA
2002
IEEE
13 years 10 months ago
2002
IEEE
This paper introduces a generalized framework, termed “stochastic cloning,” for processing relative state measurements within a Kalman filter estimator. The main motivation a...
ROBOCUP
2007
Springer
13 years 12 months ago
2007
Springer
In this article the classical self-localization approach is improved by estimating, independently from the robot’s pose, the robot’s odometric error and the landmarks’ poses....
RAS
2000
13 years 5 months ago
2000
A solution to the problem of simultaneously extracting and tracking a piecewise-linear range representation of a mobile robot's local environment is presented. The classical ...
UAI
2000
13 years 7 months ago
2000
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
ICRA
1999
IEEE
13 years 10 months ago
1999
IEEE
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...