Sciweavers

43 search results - page 7 / 9
» Fast Reinforcement Learning for Vision-guided Mobile Robots
Sort
View
ICRA
2010
IEEE
153views Robotics» more  ICRA 2010»
13 years 3 months ago
Learning to navigate through crowded environments
— The goal of this research is to enable mobile robots to navigate through crowded environments such as indoor shopping malls, airports, or downtown side walks. The key research ...
Peter Henry, Christian Vollmer, Brian Ferris, Diet...
ICRA
1999
IEEE
126views Robotics» more  ICRA 1999»
13 years 9 months ago
Monte Carlo Localization for Mobile Robots
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...
Frank Dellaert, Dieter Fox, Wolfram Burgard, Sebas...
AR
2005
138views more  AR 2005»
13 years 5 months ago
On actively closing loops in grid-based FastSLAM
Acquiring models of the environment belongs to the fundamental tasks of mobile robots. In the past, several researchers have focused on the problem of simultaneous localization an...
Cyrill Stachniss, Dirk Hähnel, Wolfram Burgar...
RAS
2010
164views more  RAS 2010»
13 years 3 months ago
Bridging the gap between feature- and grid-based SLAM
One important design decision for the development of autonomously navigating mobile robots is the choice of the representation of the environment. This includes the question which...
Kai M. Wurm, Cyrill Stachniss, Giorgio Grisetti
ICRA
2000
IEEE
111views Robotics» more  ICRA 2000»
13 years 9 months ago
Learning Globally Consistent Maps by Relaxation
Mobile robots require the ability to build their own maps to operate in unknown environments. A fundamental problem is that odometry-based dead reckoning cannot be used to assign ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro