Abstract
Automated acquisition of friction data is an interesting approach to more successfully bridge the reality gap in simulation than conventional mathematical models. To advance this area of research, we present a novel inexpensive computer vision platform as a solution for collecting and processing friction data, and we make available the open source software and data sets collected with our vision robotic approach. This paper is focused on gathering data on anisotropic static friction behavior as this is ideal for inexpensive vision approach we propose. The data set and experimental setup provide a solid foundation for a wider robotics simulation community to conduct their own experiments.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2019 16th Conference on Computer and Robot Vision, CRV 2019 |
| Number of pages | 7 |
| Publisher | IEEE |
| Publication date | May 2019 |
| Pages | 159-165 |
| Article number | 8781610 |
| ISBN (Electronic) | 9781728118383 |
| DOIs | |
| Publication status | Published - May 2019 |
| Event | 16th Conference on Computer and Robot Vision, CRV 2019 - Kingston, Canada Duration: 29 May 2019 → 31 May 2019 |
Conference
| Conference | 16th Conference on Computer and Robot Vision, CRV 2019 |
|---|---|
| Country/Territory | Canada |
| City | Kingston |
| Period | 29/05/2019 → 31/05/2019 |
| Sponsor | Canadian Image Processing and Pattern Recognition Society / Association Canadienne de Traitement d�Images et de Reconnaissance des Formes (CIPPRS/ACTIRF) |
Keywords
- Automated friction measurement
- Computer vision
- Friction
- Robot arm
- Static friction