Imitation Learning for Nonprehensile Manipulation Through Self-Supervised Learning Considering Motion Speed-Reference-Cited by-同舟云学术

Imitation Learning for Nonprehensile Manipulation Through Self-Supervised Learning Considering Motion Speed

Published:2022 Issue: Volume:10 Page:68291-68306
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Saigusa Yuki¹^ORCID,Sakaino Sho²^ORCID,Tsuji Toshiaki³^ORCID

Affiliation:

1. Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Japan

2. Department of Intelligent Interactive Systems, University of Tsukuba, Tsukuba, Japan

3. Graduate School of Science and Engineering, Saitama University, Saitama, Japan

Funder

Adaptable and Seamless Technology Transfer Program through Target-driven Research and Development (A-STEP) from the Japan Science and Technology Agency

Japan Society for the Promotion of Science by a Grant-in-Aid for Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09804696.pdf?arnumber=9804696

Reference55 articles.

1. A DMPs-Based Framework for Robot Learning and Generalization of Humanlike Variable Impedance Skills

2. Object Recognition, Dynamic Contact Simulation, Detection, and Control of the Flexible Musculoskeletal Hand Using a Recurrent Neural Network With Parametric Bias

3. Simultaneous Planning for Item Picking and Placing by Deep Reinforcement Learning

4. Deep spatial autoencoders for visuomotor learning

5. Rearrangement with Nonprehensile Manipulation Using Deep Reinforcement Learning

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