Adaptive Optimal Stochastic Trajectory Planning

Andreas Aurnhammer and Kurt Marti
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Andreas Aurnhammer: Universität der Bundeswehr München, Institut für Mathematik und Informatik
Kurt Marti: Universität der Bundeswehr München, Institut für Mathematik und Informatik

A chapter in Online Optimization of Large Scale Systems, 2001, pp 521-543 from Springer

Abstract: Abstract In Optimal Stochastic Trajectory Planning of industrial or service robots the problem can be modelled by a variational problem under stochastic disturbances that compared to ordinary deterministic engineering techniques also accounts for stochastic model parameters. Using stochastic optimisation theory, this variational problem is transformed into a nonlinear mathematical program, that can be solved by means of standard optimisation routines like SQP. However, these methods are not applicable in the on-line control process of robots, since they are not capable of solving mathematical programs in real-time. Hence, Neural Networks are trained based on solutions obtained from a standard optimisation algorithm.

Keywords: Path Planning; Configuration Space; Trajectory Planning; Chance Constraint; Path Parameter (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1007/978-3-662-04331-8_27

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