CFP: Variable Impedance Control And Learning In Complex Interaction Scenarios: Challenges And Opportunities

Motivation

Advancements in robotics research are allowing robots to move from traditional caged environments on factory floors into human environments, which are highly unstructured, dynamic, and uncertain. Such a move requires robots to autonomously interact with their environment and physically cooperate with people, which significantly increases the demand for reliable perception, planning and control. However, there are still several fundamental research problems that must addressed to ensure the success of robots in human-inhabited environment, for example: how to design physical interaction control systems that can work with potentially uncertain environment models and uncertain sensory feedback; how to deal with unpredictable and complex physical interactions with human beings; and how to adapt the robot dynamic behavior in real-time. 

This special issue aims at collecting different points of view about learning and impedance control. In principle, the combination of these two tools can afford robots the ability to enhance their manipulation and locomotion skills in unstructured environments, as well as their capacity to handle perturbations and uncertainty during physical interaction. Enabling robots to acquire knowledge autonomously and use it to interact with the world around them more intelligently will lead to future developments in this area, enforcing safety and reliability while building upon the principles of AI.

 

List of topics

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

  • Variable impedance control (VIC).
  • Low-level control of variable impedance.
  • Human impedance.
  • Physical human-robot cooperation.
  • Physical interaction control.
  • VIC from geometry awareness and manifold learning perspective.
  • Variable and optimal impedance strategies for manipulation and locomotion.

 

Timeline

The special issue will follow the following timeline:

1 October 2021

Call for Papers                                   

1 February 2022

Papercept open for submission

24 February 2022    

Submission deadline                               

21 May 2022

Authors receive RA-L reviews and recommendation   

4 June 2022

Authors of accepted MS submit final RA-L version  

20 June 2022

Authors of R&R MS resubmit revised MS            

25 July 2022

Authors receive final RA-L decision               

8 Aug 2022

Authors submit final RA-L files                   

13 Aug 2022

Camera ready version appears in RA-L on Xplore    

23 Aug 2022

Final Publication

 

Guest Editors

fares

  Name:  Fares J. Abu-Dakka
  Affiliation: Intelligent Robotics Group, Department of Electrical Engineering and Automation, Aalto University  
  e-mail:fares.abu-dakka@aalto.fi

matteo

  Name: Matteo Saveriano
  Affiliation:  Department of Computer Science and Digital Science Center, University of Innsbruck, Innsbruck, Austria.
  e-mail: matteo.saveriano@uibk.ac.at

meghan

  Name: Meghan E. Huber
  Affiliation: Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst
  e-mail:mehuber@umass.edu

thiago

  Name:  Thiago Boaventura Cunha
  Affiliation:Mechanical Engineering Department, São Carlos School of Engineering, University of São Paulo
  e-mail: tboaventura@usp.br