Browsing by Author "Hägele, David"

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    Visual analytics for nonlinear programming in robot motion planning
    (2022) Hägele, David; Abdelaal, Moataz; Oguz, Ozgur S.; Toussaint, Marc; Weiskopf, Daniel
    Nonlinear programming is a complex methodology where a problem is mathematically expressed in terms of optimality while imposing constraints on feasibility. Such problems are formulated by humans and solved by optimization algorithms. We support domain experts in their challenging tasks of understanding and troubleshooting optimization runs of intricate and high-dimensional nonlinear programs through a visual analytics system. The system was designed for our collaborators’ robot motion planning problems, but is domain agnostic in most parts of the visualizations. It allows for an exploration of the iterative solving process of a nonlinear program through several linked views of the computational process. We give insights into this design study, demonstrate our system for selected real-world cases, and discuss the extension of visualization and visual analytics methods for nonlinear programming.
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    Visualizing Optimization Trajectories
    (2019) Hägele, David
    Nonlinear constraint optimization has many applications in technical, scientific as well as economic fields. Understanding solver behavior can help to improve solvers, choose appropriate hyperparameters, and formulate better performing nonlinear programs. This thesis proposes a visual analytics tool for analyzing constraint optimization problems. The optimization process is depicted by a set of two-dimensional trajectories, representing the trace of intermediate solutions during the optimization process. This allows us to obtain an overview of the evolution of the optimization process. To support detailed analysis, supplemental views are added to show the constraints violations and areas of feasible solution. Furthermore, different interaction techniques are implemented to facilitate the exploration process. To showcase the usefulness of the approach, findings from an exemplary analysis based on optimization logs of robot motion planning are presented.