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IDA
2003
Springer
15 years 2 months ago
A Semi-supervised Method for Learning the Structure of Robot Environment Interactions
For a mobile robot to act autonomously, it must be able to construct a model of its interaction with the environment. Oates et al. developed an unsupervised learning method that pr...
Axel Großmann, Matthias Wendt, Jeremy Wyatt
AROBOTS
2008
158views more  AROBOTS 2008»
14 years 9 months ago
Learning traversability models for autonomous mobile vehicles
Autonomous mobile robots need to adapt their behavior to the terrain over which they drive, and to predict the traversability of the terrain so that they can effectively plan thei...
Michael Shneier, Tommy Chang, Tsai Hong, William P...
ICRA
2009
IEEE
126views Robotics» more  ICRA 2009»
15 years 4 months ago
Leaving Flatland: Toward real-time 3D navigation
— We report our first experiences with Leaving Flatland, an exploratory project that studies the key challenges of closing the loop between autonomous perception and action on c...
Benoit Morisset, Radu Bogdan Rusu, Aravind Sundare...
ICRA
2009
IEEE
117views Robotics» more  ICRA 2009»
14 years 7 months ago
Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach
The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for ca...
Matthias Tuma, Ioannis Iossifidis, Gregor Schö...
TSMC
2010
14 years 4 months ago
Interactive Teaching for Vision-Based Mobile Robots: A Sensory-Motor Approach
Abstract--For the last decade, we have developed a visionbased architecture for mobile robot navigation. Our bio-inspired model of the navigation has proved to achieve sensory-moto...
Christophe Giovannangeli, Philippe Gaussier