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» Bayesian Landmark Learning for Mobile Robot Localization
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ICRA
2002
IEEE
121views Robotics» more  ICRA 2002»
14 years 16 days ago
An Efficient Approach to the Simultaneous Localisation and Mapping Problem
—The simultaneous localization and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then...
Stefan B. Williams, Gamini Dissanayake, Hugh F. Du...
ICRA
2009
IEEE
132views Robotics» more  ICRA 2009»
14 years 2 months ago
Smoothed Sarsa: Reinforcement learning for robot delivery tasks
— Our goal in this work is to make high level decisions for mobile robots. In particular, given a queue of prioritized object delivery tasks, we wish to find a sequence of actio...
Deepak Ramachandran, Rakesh Gupta
AUTOMATICA
2011
13 years 2 months 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
ICML
1996
IEEE
14 years 8 months ago
Passive Distance Learning for Robot Navigation
Autonomous mobile robots need good models of their environment, sensors and actuators to navigate reliably and efficiently. While this information can be supplied by humans, or le...
Sven Koenig, Reid G. Simmons
AROBOTS
2002
91views more  AROBOTS 2002»
13 years 7 months ago
Fast, On-Line Learning of Globally Consistent Maps
To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro