Annual Report 2002 - Örebro universitet

Annual Report 2002 41
2.2 Mobile Robotics Lab
Our objective is to advance the state-of-the-art in the synthesis of intelligent physical agents
capable of autonomous operation in natural environments. The world "natural" denotes real
world environments that have not been specifically modified to accommodate the agents.
These systems must incorporate motor and perceptual processes to interface with the physical
world, and abstract cognitive processes to reason about the world and the available options.
2.2.1 Focus
The focus of the research performed in this laboratory is on the crucial problem of the
integration of cognitive processes into a physically embedded reasoning system. In particular,
we address three specific, important facets of the integration problem:
1. The integration between abstract reasoning about actions and goals, and the performance
of physical action;
2. The integration between models of the world used at different levels of abstractions; and
3. The integration between the symbols used by the reasoning processes to denote physical
objects, and the perceptual data corresponding to these objects.
The methodology adopted is based on the tight integration between interdisciplinary
investigation, formal analysis, and practical experimentation. The experiments are to be
conducted on different tasks, including: (i) observation, navigation, and manipulation in
complex real-world environments; (ii) robot-human cooperation, where the sensori-motoric
and cognitive abilities are distributed between the robot and the human; and (iii) teams of
cooperating robots, where these abilities are distributed among robots.
2.2.2 Research Projects
Project: Hybrid Maps
Project leader: Pär Buschka
Project staff: Alessandro Saffiotti, Tom Duckett (from
the Learning Systems Lab).
Funding: Faculty. Pär Buschka is funded by the KK
Foundation.
Cooperation: AASS Learning Systems Lab; ENST (Ecole
National Superieure de Telecommunications)
Paris, France.
Synopsis:
Autonomous mobile robots need to use spatial information about the environment in order to
effectively plan and execute navigation tasks. This information can be represented at different
level of abstractions and of locality. Each level is adequate for some sub-tasks, but not for