Abstract
In this work we introduce a technique for a humanoid robot to autonomously learn the representations of objects within its visual environment. Our approach involves an attention mechanism in association with feature based segmentation that explores the environment and provides object samples for training. These samples are learned for further object identification using Cartesian Genetic Programming (CGP). The learned identification is able to provide robust and fast segmentation of the objects, without using features. We showcase our system and its performance on the iCub humanoid robot.
Original language | English |
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Title of host publication | 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL 2012 |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 186-191 |
Number of pages | 6 |
ISBN (Print) | 9781467349635 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL) 2012 - San Diego, United States of America Duration: 7 Nov 2012 → 9 Nov 2012 https://ieeexplore.ieee.org/xpl/conhome/6384412/proceeding (Proceedings) |
Conference
Conference | IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL) 2012 |
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Abbreviated title | ICDL 2012 |
Country/Territory | United States of America |
City | San Diego |
Period | 7/11/12 → 9/11/12 |
Internet address |