Name
Abstract | ||
|---|---|---|
Today's industrial robots require expert knowledge and are not profitable for small and medium sized enterprises with their small lot sizes. It is our strong belief that more intuitive robot programming in an augmented reality robot work cell can dramatically simplify re-programming and leverage robotics technology in short production cycles. In this paper, we present a novel augmented reality system for defining virtual obstacles, specifying tool positions, and specifying robot tasks. We evaluate the system in a user study and, more specifically, investigate the input of robot end-effector orientations in general. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICRA.2014.6907747 | Robotics and Automation |
Keywords | Field | DocType |
augmented reality,collision avoidance,end effectors,industrial robots,robot programming,augmented reality robot work cell,industrial robot,intuitive robot programming,intuitive robot task,robot end-effector orientation,robotics technology,small-and-medium sized enterprise,virtual obstacle | Robot learning,Social robot,Robot control,Simulation,Personal robot,Augmented reality,Control engineering,Human–computer interaction,Engineering,Mobile robot,Ubiquitous robot,Articulated robot | Conference |
Volume | Issue | ISSN |
2014 | 1 | 1050-4729 |
Citations | PageRank | References |
9 | 0.83 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andre Gaschler | 1 | 135 | 9.32 |
| Maximilian Springer | 2 | 9 | 0.83 |
| Markus Rickert | 3 | 217 | 22.78 |
| Alois Knoll Knoll | 4 | 1700 | 271.32 |