A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF
Applied Intelligence
Coevolution of active vision and feature selection
Biological Cybernetics
Robot Navigation by Panoramic Vision and Attention Guided Fetaures
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
To Afford or Not to Afford: A New Formalization of Affordances Toward Affordance-Based Robot Control
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Learning traversability models for autonomous mobile vehicles
Autonomous Robots
Autonomous off-road navigation with end-to-end learning for the LAGR program
Journal of Field Robotics - Special Issue on LAGR Program, Part I
Robotics and Autonomous Systems
DEVLRN '09 Proceedings of the 2009 IEEE 8th International Conference on Development and Learning
Learning Object Affordances: From Sensory--Motor Coordination to Imitation
IEEE Transactions on Robotics
Goal emulation and planning in perceptual space using learned affordances
Robotics and Autonomous Systems
Terrain traversability analysis methods for unmanned ground vehicles: A survey
Engineering Applications of Artificial Intelligence
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The concept of affordances, introduced in psychology by J. J. Gibson, has recently attracted interest in the development of cognitive systems in autonomous robotics. In earlier work (Sahin, Çakmak, Dogar, Ugur, & 脙聹çoluk), we reviewed the uses of this concept in different fields and proposed a formalism to use affordances at different levels of robot control. In this article, we first review studies in ecological psychology on the learning and perception of traversability in organisms and describe how the existence of traversability was judged to exist. We then describe the implementation of one part of the affordance formalism for the learning and perception of traversability affordances on a mobile robot equipped with range sensing ability. Through experiments inspired by ecological psychology, we show that the robot, by interacting with its environment, can learn to perceive the traversability affordances. Moreover, we claim that three of the main attributes that are commonly associated with affordances, that is, affordances being relative to the environment, providing perceptual economy, and providing general information, are simply consequences of learning from the interactions of the robot with the environment.