Visualization of Nonlinear Programming for Robot Motion Planning

• Published in: arXiv.org
• Main Authors: Hägele, David, Abdelaal, Moataz, Oguz, Ozgur S, Toussaint, Marc, Weiskopf, Daniel
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 28.01.2021
• Subjects: Algorithms; Computer Science - Human-Computer Interaction; Computer Science - Numerical Analysis; Computer Science - Robotics; Domains; Mathematics - Numerical Analysis; Motion planning; Nonlinear analysis; Nonlinear programming; Optimization; Problem solving; Robot dynamics; Robotics; Subject specialists; Troubleshooting
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2101.12075

Nonlinear programming targets nonlinear optimization with constraints, which is a generic yet complex methodology involving humans for problem modeling and algorithms for problem solving. We address the particularly hard challenge of supporting domain experts in handling, understanding, and trouble-shooting high-dimensional optimization with a large number of constraints. Leveraging visual analytics, users are supported in exploring the computation process of nonlinear constraint optimization. Our system was designed for robot motion planning problems and developed in tight collaboration with domain experts in nonlinear programming and robotics. We report on the experiences from this design study, illustrate the usefulness for relevant example cases, and discuss the extension to visual analytics for nonlinear programming in general.