Learning and Control for Robot Compliant Manipulation with Human in the Loop


This Special Issue is motivated by recent developments of robotic control methods, learning algorithms and relevant technologies for compliant manipulation. A large number of researchers have reported their significant contributions to this topic. However, there lacks a Special Issue of any relevant journal concentrating on this interesting topic. We believe that the cognitive and learning abilities as well as intelligent control methods are very important in the development of the next generation of robots of compliant manipulation, and therefore deserve to be studied and discussed in a dedicated special issue.


List of topics

Topics of interest for this special issue include and are not limited to:

  • Dynamic environment estimation and prediction
  • Machine learning-based compliant skill acquirement
  • Imitation learning and applications to robot compliant manipulation
  • Intelligent control design for robot compliant manipulation
  • Physical human robot compliant interaction
  • Optimization of human robot collaboration for compliant manufacturing automation.
  • Safety for human in the loop robot manipulation in flexible/agile manufacturing



The special issue will follow the following timeline:

16 Sep 2021

Papercept open for submission

6 Oct 2021

Submission deadline                              

31 Dec 2021

Authors receive RA-L reviews and recommendation  

14 Jan 2022

Authors of accepted MS submit final RA-L version 

30 Jan 2022

Authors of R&R MS resubmit revised MS           

6 Mar 2022

Authors receive final RA-L decision              

20 Mar 2022

Authors submit final RA-L files                  

25 Mar 2022

Camera ready version appears in RA-L on Xplore   

5 April 2022

Final Publication


Guest Editors

Chenguang Yang Name: Chenguang Yang
Affiliation: Bristol Robotics Laboratory, UWE Bristol, UK
e-mail: cyang@ieee.org
Miao Li Name: Miao Li
Affiliation: Wuhan University, China 
e-mail: miao.li@whu.edu.cn
Hao Ding Name: Hao Ding
Affiliation: University of Shanghai for Science and Technology, China
e-mail: hao.ding@usst.edu.cn
Andrea Zanchettin Name: Andrea M. Zanchettin
Affiliation: Politecnico di Milano, Italy   
e-mail: andreamaria.zanchettin@polimi.it
julie shaw Name: Julie A. Shah
Affiliation: Massachusetts Institute of Technology, USA
e-mail: julie_a_shah@csail.mit.edu



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