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The Intelligent Autonomous Systems Group conducts research in Artificial
Intelligence and its application to sensor-equipped, intelligent computer
systems that are embedded in the physical world. Such computer systems are
becoming increasingly important. Application domains that our group considers,
range from intelligent, camera-equipped indoor environments that adapt to the
habits of their occupants, to autonomous mobile robots that fulfill complex
tasks in office environments, to computer systems that watch football games,
analyze, and comment on them, to teams of autonomous robots playing robot
soccer.
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CoTeSys Workshop on the Kitchen Demonstration Scenario
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PSSCR'07 organized by IAS@TUM and AI@SRI!...
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In the context of these application domains our group investigates various
aspects of perceiving, reasoning about, and executing complex and natural
activities. Being capable of competently dealing with activities is an
essential prerequisite in the realization of integrated intelligent systems.
Intelligent systems must be able to recognize and understand the activities of
the agents in their environments as well as to manage their own activities and
produce high performance behavior for achieving them. To realize these
capabilities, we study computational mechanisms and develop integrated systems
that (1) can make use of plans for improved control of autonomous robots,
(2) perceive, interpret, and analyze single and multi agent activities,
(3) learn to perform complex physical activities competently, and
(4) represent and reason about activities.
In the realization of such intelligent systems, we emphasize
integrated system research. In integrated system research we focus on
specific comprehensive tasks and aim at developing complete hardware
and software systems that can solve these tasks by perceiving their
environments and acting in them. The salient characteristics of
integrated system research are that research questions are derived
from the systems' tasks, sensing-, and action capabilities and
that computational mechanisms are validated and empirically studied in
the context of the complete systems.
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