English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The transition to agile manufacturing, Industry 4.0, and high-mix-low-volumetasks require robot programming solutions that are flexible. However, mostdeployed robot solutions are still statically programmed and use stiff positioncontrol, which limit their usefulness. In this paper, we show how a singlerobot skill that utilizes knowledge representation, task planning, andautomatic selection of skill implementations based on the input parameters canbe executed in different contexts. We demonstrate how the skill-based controlplatform enables this with contact-rich wiping tasks on different robotsystems. To achieve that in this case study, our approach needs to addressdifferent kinematics, gripper types, vendors, and fundamentally differentcontrol interfaces. We conducted the experiments with a mobile platform thathas a Universal Robots UR5e 6 degree-of-freedom robot arm with position controland a 7 degree-of-freedom KUKA iiwa with torque control.

Using Knowledge Representation and Task Planning for Robot-agnostic Skills on the Example of Contact-Rich Wiping Tasks