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Robust Execution for Stochastic Hybrid Systems
Algorithms for Control, Estimation and Learning
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Unmanned systems, such as Autonomous Underwater Vehicles §(AUVs), planetary rovers and space probes, have§enormous potential §in areas such as reconnaissance and space§exploration. However the §effectiveness and robustness of these systems is§currently restricted §by a lack of autonomy. A model-based executive, which§increases §the level of autonomy can be used to simplify the§operator s task §and leave degrees of freedom in the plan that allow§the executive to §optimize resources and ensure robustness to uncertainty. §Uncertainty arises due to uncertain state estimation,§disturbances, §model uncertainty and component failures. This book§develops a §model-based executive that reasons explicitly from§a stochastic hybrid discrete-continuous system model§to find the §optimal course of action, while ensuring the required§level of §robustness to uncertainty is achieved. The executive§makes use of §new algorithms for control, estimation and learning§of stochastic §systems, which are presented in this book.
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