In this work, we model context in terms of a set of concepts grounded in a robot's sensorimotor interactions with the environment. For this end, we treat context as a latent variable in Latent Dirichlet Allocation, which is widely used in computational linguistics for modeling topics in texts. The flexibility of our approach allows many-to-many relationships between objects and contexts, as well as between scenes and contexts.We use a concept web representation of the perceptions of the robot as a basis for context analysis. The detected contexts of the scene can be used for several cognitive problems. Our results demonstrate that the robot can use learned contexts to improve object recognition and planning.
|Title of host publication||2014 Joint IEEE International Conferences on Development and Learning and Epigenetic Robotics (ICDL-Epirob)|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||7|
|Publication status||Published - Dec 2014|
|Event||4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, IEEE ICDL-EPIROB 2014 - Genoa, Italy|
Duration: 13 Oct 2014 → 16 Oct 2014
|Conference||4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, IEEE ICDL-EPIROB 2014|
|Period||13/10/14 → 16/10/14|
Bibliographical noteWe would like to thank Angelo Cangelosi, Anna Borghi
and Honghai Liu for fruitful discussions on the integrating
context in cognitive systems. This work is partially funded by
the Scientific and Technological Research Council of Turkey
(TUB¨ ˙ITAK) through project no 111E287.