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» Bayesian Landmark Learning for Mobile Robot Localization
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ICRA
2008
IEEE
124views Robotics» more  ICRA 2008»
14 years 2 months ago
Simultaneous learning of motion and sensor model parameters for mobile robots
— Motion and sensor models are crucial components in current algorithms for mobile robot localization and mapping. These models are typically provided and hand-tuned by a human o...
Teddy N. Yap Jr., Christian R. Shelton
UAI
2003
13 years 9 months ago
The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach
We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-bui...
Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Ko...
IJRR
2010
185views more  IJRR 2010»
13 years 6 months ago
FISST-SLAM: Finite Set Statistical Approach to Simultaneous Localization and Mapping
The solution to the problem of mapping an environment and at the same time using this map to localize (the simultaneous localization and mapping, SLAM, problem) is a key prerequis...
Bharath Kalyan, K. W. Lee, W. Sardha Wijesoma
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 2 months 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...
AROBOTS
2010
194views more  AROBOTS 2010»
13 years 6 months ago
Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of Bayesian filters
Abstract Modern service robots will soon become an essential part of modern society. As they have to move and act in human environments, it is essential for them to be provided wit...
Nicola Bellotto, Huosheng Hu