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» Bayesian Landmark Learning for Mobile Robot Localization
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ICRA
2005
IEEE
128views Robotics» more  ICRA 2005»
14 years 1 months ago
Vibration-based Terrain Analysis for Mobile Robots
—Safe, autonomous mobility in rough terrain is an important requirement for planetary exploration rovers. Knowledge of local terrain properties is critical to ensure a rover’s ...
Christopher A. Brooks, Karl Iagnemma, Steven Dubow...
VISAPP
2007
13 years 8 months ago
Extraction of multi-modal object representations in a robot vision system
We introduce one module in a cognitive system that learns the shape of objects by active exploration. More specifically, we propose a feature tracking scheme that makes use of the...
Nicolas Pugeault, Emre Baseski, Dirk Kraft, Floren...
IROS
2006
IEEE
168views Robotics» more  IROS 2006»
14 years 1 months ago
An Entropy-Based Measurement of Certainty in Rao-Blackwellized Particle Filter Mapping
– In Bayesian based approaches to mobile robot simultaneous localization and mapping, Rao-Blackwellized particle filters (RBPF) enable the efficient estimation of the posterior b...
Jose-Luis Blanco, Juan-Antonio Fernandez-Madrigal,...
RAS
2006
138views more  RAS 2006»
13 years 7 months ago
From pixels to multi-robot decision-making: A study in uncertainty
Mobile robots must cope with uncertainty from many sources along the path from interpreting raw sensor inputs to behavior selection to execution of the resulting primitive actions...
Peter Stone, Mohan Sridharan, Daniel Stronger, Gre...
ICML
2006
IEEE
14 years 8 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal