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search.filters.applied.f.access: openAccess × Author: Henrion, René × Author: Hömberg, Dietmar × Type: Text × Publisher: Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik ×

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    Path planning and collision avoidance for robots : dedicated to Prof. Dr. Helmut Maurer on the occasion of his 65th birthday
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2011) Gerdts, Matthias; Henrion, René; Hömberg, Dietmar; Landry, Chantal; Maurer, Helmut
    An optimal control problem to find the fastest collision-free trajectory of a robot surrounded by obstacles is presented. The collision avoidance is based on linear programming arguments and expressed as state constraints. The optimal control problem is solved with a sequential programming method. In order to decrease the number of unknowns and constraints a backface culling active set strategy is added to the resolution technique.
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    Task assignment, sequencing and path-planning in robotic welding cells
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2013) Landry, Chantal; Welz, Wolfgang; Henrion, René; Hömberg, Dietmar; Skutella, Martin
    A workcell composed of a workpiece and several welding robots is considered. We are interested in minimizing the makespan in the workcell. Hence, one needs i) to assign tasks between the robots, ii) to do the sequencing of the tasks for each robot and iii) to compute the fastest collisionfree paths between the tasks. Up to now, task assignment and path-planning were always handled separately, the former being a typical Vehicle Routing Problem whereas the later is modelled using an optimal control problem. In this paper, we present a complete algorithm which combines discrete optimization techniques with collision detection and optimal control problems efficiently
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    Chance constraints in PDE constrained optimization
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2016) Farshbaf-Shaker, M. Hassan; Henrion, René; Hömberg, Dietmar
    Chance constraints represent a popular tool for finding decisions that enforce a robust satisfaction of random inequality systems in terms of probability. They are widely used in optimization problems subject to uncertain parameters as they arise in many engineering applications. Most structural results of chance constraints (e.g., closedness, convexity, Lipschitz continuity, differentiability etc.) have been formulated in a finite-dimensional setting. The aim of this paper is to generalize some of these well-known semi-continuity and convexity properties to a setting of control problems subject to (uniform) state chance constraints.