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» Learning to Drive and Simulate Autonomous Mobile Robots
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2007
152views Robotics» more  RSS 2007»
13 years 9 months ago
Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
IDA
2003
Springer
14 years 26 days 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
IROS
2007
IEEE
175views Robotics» more  IROS 2007»
14 years 1 months ago
Adaptive long range vision in unstructured terrain
— A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predict...
Ayse Erkan, Raia Hadsell, Pierre Sermanet, Jan Ben...
NPL
2007
109views more  NPL 2007»
13 years 7 months ago
Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing
Autonomous mobile robots form an important research topic in the field of robotics due to their near-term applicability in the real world as domestic service robots. These robots ...
Eric A. Antonelo, Benjamin Schrauwen, Jan M. Van C...
AROBOTS
2007
159views more  AROBOTS 2007»
13 years 7 months ago
Structure-based color learning on a mobile robot under changing illumination
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
Mohan Sridharan, Peter Stone