Adaptive Optimal Stochastic Trajectory Planning

Numerics and Real-time Application
  • Andreas Aurnhammer
  • Kurt Marti


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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Andreas Aurnhammer
    • 1
  • Kurt Marti
    • 1
  1. 1.Institut für Mathematik und InformatikUniversität der Bundeswehr MünchenGermany

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