Interpolation and optimal motion planning for mechanical systems

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Abstract
During the past few years, researchers have considered various motion planning problems for systems with nonintegrable constraints. The aim of this thesis is to formulate and study the problem of motion planning for systems with both complex dynamics and nonholonomic constraints and to develop a theory of optimal motion control for such systems. Both the kinematics and dynamics of kinematically constrained systems present challenges. The presence of payloads with complex internal dynamics further complicates matters. In principle, solutions can always be found. The numerical solutions of the optimal control problems under consideration turn out to be computationally difficult, although numerical solutions can be found for very special boundary conditions. For low dimensional kinematic optimal control problems, we present the optimal paths and analyze their geometry in detail. These results contribute to the growing body of knowledge concerning explicitly solvable motion control problems. For more general classes of problems, we appeal to interpolation strategies. While it is relatively simple to find motions within suitably restricted classes of interpolating functions, it is necessary to understand how far such solutions are from optimality with respect to some reasonable criterion. Specifically, polynomial interpolants work very well when applied carefully to the mechanical systems considered in this thesis. In addition: the methods we propose: result in near optimal trajectories which can be readily computed and used in real time applications.
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