Visualization of Nonlinear Programming for Robot Motion Planning
Abstract
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.
Keywords
Cite
@article{arxiv.2101.12075,
title = {Visualization of Nonlinear Programming for Robot Motion Planning},
author = {David Hägele and Moataz Abdelaal and Ozgur S. Oguz and Marc Toussaint and Daniel Weiskopf},
journal= {arXiv preprint arXiv:2101.12075},
year = {2021}
}
Comments
8 pages, 6 figures