Robotic technologies are permeating all aspects of manufacturing systems as well as other fields, expediting the generation of flexible manipulations. Though great progress has been achieved for robotic manipulation, robust autonomous robotic grasping and manipulation at a level approaching human skills remains an elusive goal. One reason is the difficulty in dealing with the inevitable uncertainties and unforeseen situations encountered in dynamic and unstructured application environments. Unknown information required to plan grasps such as object shape and pose needs to be extracted from the environment through sensors. An efficient and forefront design of advanced robots requires solving a compromise among size and weight, functional dexterity and control complexity. Basically, this comes down to choosing the optimal number and placement of sensors and motors as well as the motion couplings and the mechanical compliance. The bio-inspired embodiment in fine manipulation exhibit significant advantages to tackle such difficulties. Advanced mechanical designs such as soft actuation, under-actuated mechanisms and hyper-redundant continuum robots together with multimodal distributed sensing, machine learning algorithms and reactive control might exhibit enhanced capabilities of adapting to changing environments and learning from exploration.
Currently, the great progress has been making in fine manipulation to recreate grasping the stuff, feeling a light touch, shaking hands, touching other people, etc. and to act it naturally. However, fine manipulation is quite sophisticated compared to controlling a classical mechanical system. The aim of this special issue is to understand how human acquires dexterity in object manipulation, discuss the possibility of its application in robotic systems, and to draw key strategies for dealing with robotic dexterous manipulation in next generation. The level of dexterous manipulation by robots is currently far from that of human being. What can improve the ability of robots? One hint might be to understand the approaches of human being in dexterity acquisition.
The special section addresses a broad spectrum of topics within mechatronic design of smart robots with embodied intelligence. Special attention should be given to the integration of mechatronic design with control efficiency and simplification and autonomous enhanced capabilities. This includes mechanism modeling and design, new actuation concepts, innovative transmission systems and actuation networks, novel sensors and sensing allocation, learning techniques and adaptive/reactive control algorithms. The scenarios of interest cover all the field of robotics and thus go from medical to industrial applications.
- Tactile-driven exploration strategies
- Tactile servoing and manipulation
- Tactile image and tactile object perception
- Tactile-based unknown object grasp and in-hand manipulations
- Multi-modal perception for fine manipulation
- Collaborative perception for fine manipulation
- Advanced control method for fine manipulation
- Coordinated control for fine manipulation
- End-to-end control architecture for fine manipulation
- Mind-controlled fine manipulation
- Cognitive mechanisms of fine manipulation and deep learning and its application
- Using tactile for unknown object reconstruction, classification and slip detection
- Whole-body sensing based manipulation and safety
Follow the guidelines in "Information for Authors" in the IEEE-IES website: http://www.ieee-ies.org/pubs/transactions-on-industrial-informatics. Please submit your manuscript in electronic form through Manuscript Central web site: https://mc.manuscriptcentral.com/tii. On the submitting page #1 in popup menu of manuscript type, select: SS on Bio-inspired Embodiment for Intelligent Sensing and Dexterity in Fine Manipulation.
|Deadline for manuscript submissions||Extented to Feb.28, 2018|
|Expected publication date (tentative)||June 2018|
- Prof. Zhijun Li, South China University of Technology, University of Science and Technology of China, firstname.lastname@example.org
- Dr. Huaping Liu, Tsinghua University, China, email@example.com
- Dr. Fanny Ficuciello, DIETI, University of Naples Federico II, Italy, firstname.lastname@example.org