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 present a multimodal mobile teleoperation system thatconsists of a novel vision-based hand pose regression network (Transteleop) andan IMU-based arm tracking method. Transteleop observes the human hand through alow-cost depth camera and generates not only joint angles but also depth imagesof paired robot hand poses through an image-to-image translation process. Akeypoint-based reconstruction loss explores the resemblance in appearance andanatomy between human and robotic hands and enriches the local features ofreconstructed images. A wearable camera holder enables simultaneous hand-armcontrol and facilitates the mobility of the whole teleoperation system. Networkevaluation results on a test dataset and a variety of complex manipulationtasks that go beyond simple pick-and-place operations show the efficiency andstability of our multimodal teleoperation system.

A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU