Modelling and Simulation for High Autonomy Systems
Abstract
The basic objective of this research is to develop architectures for systems
capable of highly autonomous behavior by combining decision, perception, and
action components. The major challenge of this dissertation is the integration
of high-level symbolic (AI) models with low-level dynamic (control-theoretic)
models into a coherent model base. The systematic inclusion of dynamic and
symbolic models each dedicated to support a single function such as planning,
operation, diagnosis or recovery allows us to extend existing multi-layered
control and information architectures. A knowledge-based simulation environment
is employed to simulate and verify the proposed integrated model-based
architecture. Systems with high levels of autonomy are critical for unmanned,
and partially manned, space missions. The utility of the proposed high autonomy
system will be demonstrated with models of a robot-managed fluid handling
laboratory for International Space Station Freedom. NASA engineers will be able
to base designs of intelligent controllers for such systems on the architecture
developed in this dissertation. They will be able to employ our tools and
simulation environment to verify such designs prior to their implementation.
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Last modified: December 8, 2005 -- © François Cellier