From Simulation to Reality: A Learning Framework for Fish-Like Robots to Perform Control Tasks-Reference-Cited by-同舟云学术

From Simulation to Reality: A Learning Framework for Fish-Like Robots to Perform Control Tasks

Published:2022-12 Issue:6 Volume:38 Page:3861-3878
ISSN:1552-3098
Container-title:IEEE Transactions on Robotics
language:
Short-container-title:IEEE Trans. Robot.

Author:

Zhang Tianhao¹^ORCID,Tian Runyu¹,Yang Hongqi¹,Wang Chen²^ORCID,Sun Jinan²,Zhang Shikun²,Xie Guangming¹^ORCID

Affiliation:

1. State Key Laboratory of Turbulence and Complex Systems, Intelligent Biomimetic Design Lab, College of Engineering, Peking University, Beijing, China

2. National Engineering Research Center of Software Engineering, Peking University, Beijing, China

Funder

National Natural Science Foundation of China

Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8860/9970416/09802680.pdf?arnumber=9802680

Reference44 articles.

1. Dealing with sparse rewards in reinforcement learning;hare,2019

2. A Guiding Vector-Field Algorithm for Path-Following Control of Nonholonomic Mobile Robots

3. Mesh deformation based on radial basis function interpolation

4. Ship motions using single-phase level set with dynamic overset grids

5. Parallel computing strategy for a flow solver based on immersed boundary method and discrete stream-function formulation

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