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

In this paper, we propose an approach to detect incipient slip, i.e. predictslip, by using a high-resolution vision-based tactile sensor, GelSlim. Thesensor dynamically captures the tactile imprints of the contact object andtheir changes with a soft gel pad. The method assumes the object is mostlyrigid and treats the motion of object's imprint on sensor surface as a 2Drigid-body motion. We use the deviation of the true motion field from that of a2D planar rigid transformation as a measure of slip. The output is a dense slipfield which we use to detect when small areas of the contact patch start toslip (incipient slip). The method can detect both translational and rotationalincipient slip without any prior knowledge of the object at 24 Hz. We test themethod on 10 objects 240 times and achieve 86.25% detection accuracy. Wefurther show how the slip feedback can be used to monitor the gripping force toavoid slip with a closed-loop bottle-cap screwing and unscrewing experimentwith incipient slip detection feedback. The method was demonstrated to beuseful for the robot to apply proper gripping force and stop screwing at theright point before breaking objects. The method can be applied to manymanipulation tasks in both structured and unstructured environments.

Maintaining Grasps within Slipping Bound by Monitoring Incipient Slip