Viewpoint Selection for the Efficient Teleoperation of a Robot Arm Using Reinforcement Learning
Author:
Affiliation:
1. Department of Precision Engineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
2. Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
Funder
Japan Atomic Energy Agency (JAEA) Nuclear Energy Science and Technology (S&T) and Human Resource Development
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/ielx7/6287639/10005208/10296844.pdf?arnumber=10296844
Reference25 articles.
1. Auto-encoding variational Bayes;kingma;arXiv 1312 6114,2013
2. Recurrent world models facilitate policy evolution;ha;Proc Adv Neural Inf Process Syst,2018
3. Viewpoint Selection without Subject Experiments for Teleoperation of Robot Arm in Reaching Task Using Reinforcement Learning
4. Stochastic backpropagation and approximate inference in deep generative models;rezende;Proc Int Conf Mach Learn,2014
5. Environmental camera placements for skilled operators in unmanned construction
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