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» Learning to Drive and Simulate Autonomous Mobile Robots
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ROBOCUP
2004
Springer
147views Robotics» more  ROBOCUP 2004»
13 years 10 months ago
Learning to Drive and Simulate Autonomous Mobile Robots
We show how to apply learning methods to two robotics problems, namely the optimization of the on-board controller of an omnidirectional robot, and the derivation of a model of the...
Alexander Gloye, Cüneyt Göktekin, Anna E...
IROS
2008
IEEE
138views Robotics» more  IROS 2008»
13 years 11 months ago
Deep belief net learning in a long-range vision system for autonomous off-road driving
Abstract— We present a learning-based approach for longrange vision that is able to accurately classify complex terrain at distances up to the horizon, thus allowing high-level s...
Raia Hadsell, Ayse Erkan, Pierre Sermanet, Marco S...
ISCAS
2006
IEEE
119views Hardware» more  ISCAS 2006»
13 years 10 months ago
Using self-organizing maps to control physical robots with omnidirectional drives
— In many application areas, robots most suitably employ classical PID controllers and the like. In the field of autonomous mobile robots, however, further adaptation features a...
Ralf Salomon, Hagen Burchardt, T. Schulz
CEC
2009
IEEE
13 years 11 months ago
HyperNEAT controlled robots learn how to drive on roads in simulated environment
Abstract— In this paper we describe simulation of autonomous robots controlled by recurrent neural networks, which are evolved through indirect encoding using HyperNEAT algorithm...
Jan Drchal, Jan Koutník, Miroslav Snorek
IJCAI
2007
13 years 6 months ago
Online Speed Adaptation Using Supervised Learning for High-Speed, Off-Road Autonomous Driving
The mobile robotics community has traditionally addressed motion planning and navigation in terms of steering decisions. However, selecting the best speed is also important – be...
David Stavens, Gabriel Hoffmann, Sebastian Thrun