Visual analytics for nonlinear programming in robot motion planning
| Autor: | Moataz Abdelaal, Ozgur S. Oguz, Marc Toussaint, Daniel Weiskopf, David Hägele |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Visual analytics
Computer science business.industry Process (engineering) Troubleshooting Extension (predicate logic) visual analytics Condensed Matter Physics Nonlinear programming Visualization Domain (software engineering) Nonlinear system nonlinear programming loss landscape Artificial intelligence Electrical and Electronic Engineering 000 Informatik Informationswissenschaft allgemeine Werke::000 Informatik Wissen Systeme::004 Datenverarbeitung Informatik business optimization design study |
| Popis: | 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. Deutsche Forschungsgemeinschaft Projekt DEAL |
| Databáze: | OpenAIRE |
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