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Topic: Challenges in Robotic Task Learning: a Focus on Control Approaches

A special issue of Complex Engineering Systems

ISSN 2770-6249 (Online)

Submission deadline: 15 Feb 2023

Guest Editor(s)

  • Prof. Loris Roveda
    Faculty of Engineering of eCampus University & Researcher at Istituto Dalle Molle di studi sull’Intelligenza Artificiale, Università della Svizzera Italiana, Manno, Switzerland.

    Website | E-mail

  • Prof. Hamid Reza Karimi
    Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy.

    Website | E-mail

Special Issue Introduction

Providing intelligence to robotics systems is a hot topic nowadays. While many advances have been made in low-level and mid-level robot control, there is still a need to conceive high-level controllers that can properly sense, perceive, and interact with the surrounding environments. Nevertheless, while research is now focused on this challenging point, current robots still do not show these improved capabilities that enable them to perform truly complex applications in unstructured and evolving environments.

The special issue focuses on the topic of providing intelligence to the robotic systems from the control point of view, developing adaptable control frameworks that would enable a robot to learn new tasks in new situations.

The following topics are of interest (not limited to):
● Intelligent control
● Task learning
● Modular control framework
● Evolving controllers
● Evolutionary learning applied to control
● Transfer learning
● Sensing and perception for adaptable learning and control
● Online planning in evolving environments

Submission Deadline

15 Feb 2023

Submission Information

Articles of special issue are free of charge for article processing.
For Author Instructions, please refer to
For Online Submission, please login at
Submission Deadline: 15 Feb 2023
Contacts: Irene Liu, Assistant Editor,

Published Articles

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