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JFR
2006
88views more  JFR 2006»
13 years 10 months ago
Discovering natural kinds of robot sensory experiences in unstructured environments
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...
CIMCA
2005
IEEE
14 years 4 months ago
Fuzzy Inference Model for Learning from Experiences and Its Application to Robot Navigation
A fuzzy inference model for learning from experiences (FILE) is proposed. The model can learn from experience data obtained by trial-and-error of a task and it can stably learn fr...
Manabu Gouko, Yoshihiro Sugaya, Hirotomo Aso
IJRR
2008
139views more  IJRR 2008»
13 years 10 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
TSMC
2010
13 years 5 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
CONNECTION
2006
91views more  CONNECTION 2006»
13 years 10 months ago
From unknown sensors and actuators to actions grounded in sensorimotor perceptions
This article describes a developmental system based on information theory implemented on a real robot that learns a model of its own sensory and actuator apparatus. There is no in...
Lars Olsson, Chrystopher L. Nehaniv, Daniel Polani