Work

Visualization of nonlinear programming for robot motion planning

Year: 2020

Type: conference-paper

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.

Source: International Symposium on Visual Information Communication and Interaction (VINCI)

DOI: 10.1145/3430036.3430050

Authors: David Hägele, Moataz Abdelaal, Ozgur S. Oguz, Marc Toussaint, Daniel Weiskopf

Institutions: University of Stuttgart, Technische Universität Berlin

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Deutsche Forschungsgemeinschaft, German Academic Exchange Service London

Award: EXC 2120: Integratives computerbasiertes Planen und Bauen für die Architektur