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» Covisibility-Based Map Learning Method for Mobile Robots
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ICRA
2008
IEEE
124views Robotics» more  ICRA 2008»
13 years 11 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
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
RAS
2008
123views more  RAS 2008»
13 years 4 months ago
Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping
This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates th...
Martin Persson, Tom Duckett, Achim J. Lilienthal
SBRN
2008
IEEE
13 years 11 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...