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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In this study, an adaptive object deformability-agnostic human-robotcollaborative transportation framework is presented. The proposed frameworkenables to combine the haptic information transferred through the object withthe human kinematic information obtained from a motion capture system togenerate reactive whole-body motions on a mobile collaborative robot.Furthermore, it allows rotating the objects in an intuitive and accurate wayduring co-transportation based on an algorithm that detects the human rotationintention using the torso and hand movements. First, we validate the frameworkwith the two extremities of the object deformability range (i.e, purely rigidaluminum rod and highly deformable rope) by utilizing a mobile manipulatorwhich consists of an Omni-directional mobile base and a collaborative roboticarm. Next, its performance is compared with an admittance controller during aco-carry task of a partially deformable object in a 12-subjects user study.Quantitative and qualitative results of this experiment show that the proposedframework can effectively handle the transportation of objects regardless oftheir deformability and provides intuitive assistance to human partners.Finally, we have demonstrated the potential of our framework in a differentscenario, where the human and the robot co-transport a manikin using adeformable sheet.

An Object Deformation-Agnostic Framework for Human-Robot Collaborative Transportation