RA5 Spatial cognition and multimodal situation awareness
… how can an embodied system come to a conceptualisation of sensory and
sensory-motor data, generate plans and actions to navigate and
manipulate in typical home settings...
The work at the UvA will mainly concentrate on the research activities RA1,2 and 3.:x
5.1 Hierarchical representations of space
Because metric maps do not scale
well and because a cognitive robot should be instructed at a
`conceptual’ level we need to integrate topological maps and metric
maps. In WP5.1 we study probabilistic methods for this.
5.2 Categorization of spaces and objects
In the hierarchical representation an important issue
is the categorization of sensory information. In WP 5.2 we will study
feature representations which are invariant for small rotations and
translations of the robot, but in which a good discrimination between
different spaces can be found. Since we expect that categories can be
characterized by both their appearance as well as their spatial
features we may use depth information and visual information.
Can we use graphs on local salient points for that? (Graph-Theoretical
Methods in Computer Vision
and S. Dickinson,Springer-Verlag Heidelberg Lecture Notes in
Computer Science, Volume 2292, 2002, pp 148--174.)
Can we use other local features? (Jim
Robot Localization and Mapping with Uncertainty using Scale-Invariant
Landmarks, Intl. Journal of Robotics Research, Vol. 21, No. 8, August
2002, pp. 735--758.
5.3 Learning concepts by interaction with humans
Instead of a bottom-up, data driven approach, concepts
can also be learned by interaction with humans. The robot therefore has
to recognize and track the user and have a simple speech dialogue. Also
gesture recognition needs to be implemented.
We will study different learning methods, such as
supervised learning and reinforcement learning.
Some of the work carried out by Stephan ten Hagen: (Stephan ten Hagen.
and navigation targets
In Proceedings of the 15th Dutch-Belgian Artificial Intelligence
, Nijmegen, The Netherlands, October 2003.
5.4 Models of temporal relations
study models which are well suited to deal with uncertainties in data
on temporal relations.
Dynamic Bayesian Networks will be used to model the movements of humans
in an environment. These models will be studied in the context of the
home tour scenario