Complex & Intelligent Systems - Special Issue on

Robotic Dexterous Manipulation: from Tele-operation to Autonomous Learning and Adaptive Control

*SCOPE and TOPICS*

Since the birth of the first industrial robot-Unimate, we have witnessed the rapid improvement of robotic manipulability. Many fine and complex manipulations were implemented by robotic/human-robot collaboration systems. Such manipulation has been used in industrial, service, medical and agriculture etc domains.

How to endow robots with high-level manipulation intelligence is one dream of many roboticists. In recent years, “AI powered robots” have become one slogan everyone knows. Scientists from four lines are working towards the goal of manipulation intelligence. 

• Data-driven robotic skill learning -- Researchers from AI, especially Machine Learning domain, are exploiting more powerful computer hardware and computational capability to autonomously extract intelligence factors for robots. However there are also lots of critical voices that such intelligence is unexplainable, generality is weak and learning procedures are time consuming etc.  
• Bio-inspired manipulation model recognition and inference-- Meanwhile, we have also seen recent progress on human-inspired robotic manipulation. For such methods, human’s “intelligence” is recorded and analysed from neuroscience and neuro-adaptive and control aspects, then transferred to robot platforms quickly to implement complex tasks. The main drawback of these approaches is that it is difficult to evaluate/predict the system performance with existing control analysis tools and thus their design is usually empirical and case dependent/sensitive. 
• Sensory-based robotic adaptive control-- Observations also note that sensory-based manipulation is exploiting rich sensor feedback (vision, tactile etc.)  in sound manipulation theory and thus enhanced closed loop control systems and adaptive controllers can be designed to improve the robustness of manipulation. 
• Teleoperation, Telepresence and shared autonomy -- Finally AR VR and haptic rendering technology make humans perceive the remote scenario in an immersive way, and this largely facilitates the introduction of human’s intelligence into robotic manipulation and turns out to be a fairly practical approach. However on this line, safe and reliable haptic technical system development, bilateral perception and control for human-robot systems are still a big challenge to tackle for researchers in this domain.

We believe now it is a good time to bring these all four branches into one special issue to 

●    To understand and define the state of the art of dexterous manipulation from fundamental principle and applications aspects
●    To get to know what complex manipulation have been solved by such methods
●    To find the common scientific problems/challenges for these four approaches and merge the branches to solve more complex tasks which can not be dealt with by a single method.

In this  special issue, we hope bring together experts from the different domains, including telerobotics, neurocognition and advanced control, machine learning to discuss recent progress and future challenges in robotic dexterous manipulation, and to draw a whole-scene picture of robotic manipulation with harmonic mixture of multidisciplinary research.

The topics of interests in this special issue include, but are not limited to:

●    Sensory-based manipulation
●    Data-driven robotic manipulation
●    Bio-inspired manipulation
●    Visuo-tactile manipulation
●    Modelling of human manipulation
●    Human robot collaborative manipulation
●    New haptic hardware R&D and teleoperation
●    visuo-haptic telepresence
●    AI-augmented visual servoing and applications
●    Complex manipulation applications in industrial, medical, service and agriculture 

Important dates

Submission deadline: 15th March 2021
Notification: 1st April 2021
Final version due: 1st  June 2021
To appear in the issue of: July, 2021 (tentative)

*GUEST EDITORS*

Dr. Qiang Li
Center for Cognitive Interaction Technology (CITEC) , Bielefeld University, Bielefeld, Germany
Email:qli@techfak.uni-bielefeld.de

Dr. Chao Liu
LIRMM, UMR5506, French National Center for Scientific Research (CNRS), Monptellier, France

Prof. Chenguang Yang 
Bristol Robotics Laboratory, University of the West of England, Bristol, UK 

Prof. Fei Chen 
Smart Manipulation Robots Laboratory, The Chinese University of Hong Kong, Hong Kong, China 

Prof. Helge Ritter
Center for Cognitive Interaction Technology (CITEC) , Bielefeld University, Bielefeld, Germany