Learning Dynamic Tasks on a Large-scale Soft Robot in a Handful of Trials

Authors

Daniel L. Cheney (ORCID: https://orcid.org/0009-0008-6994-7688)
Marc Peter Deisenroth (ORCID: https://orcid.org/0000-0003-1503-680X)
Yasemin Bekiroglu (ORCID: https://orcid.org/0000-0002-2597-6013)
Sicelukwanda Zwane
Curtis C. Johnson (ORCID: https://orcid.org/0000-0001-9556-9483)
Marc D. Killpack (ORCID: https://orcid.org/0000-0001-9372-104X)
Yicheng Luo

Institutions

Brigham Young University (US)
University College London (GB)

Publication Details

Published: 2024-10-14
DOI: https://doi.org/10.1109/iros58592.2024.10802122
Primary Topic: Soft Robotics and Applications
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Science Foundation
Engineering and Physical Sciences Research Council

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Learning Dynamic Tasks on a Large-scale Soft Robot in a Handful of Trials

Daniel L. Cheney, Marc Peter Deisenroth, Yasemin Bekiroglu, Sicelukwanda Zwane et al.

Oct 14, 2024

Soft Robotics and Applications

article

Learning Dynamic Tasks on a Large-scale Soft Robot in a Handful of Trials

Daniel L. Cheney, Marc Peter Deisenroth, Yasemin Bekiroglu, Sicelukwanda Zwane, Curtis C. Johnson, Marc D. Killpack, Yicheng Luo

October 14, 2024article en

Abstract

No abstract available for this paper.

Brigham Young University (US), University College London (GB)

National Science Foundation, Engineering and Physical Sciences Research Council

Openalex Percentile: Top 77%

Soft Robotics and Applications

DOI Source OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.