Intelligent Control and Robotics

Dear Colleagues,

Intelligent control and robotics are closely related to each other and have been the subject of many years of research. With the growing need of robots that can perform useful tasks for humans, human-like learning and cognitive skills are required for the upcoming intelligent robots sharing common surroundings with humans such as homes, offices, factories, and outdoor environments. In view of this, intelligent control and robotics have been evolving in such a way that the topics accommodate and take advantage of a large spectrum of convergence technologies developed from algorithmic research, symbolic AI, and computational AI using rule-based knowledge modeling, neural networks, fuzzy logic, GAs, and more recently deep neural networks. Further, since intelligent robots should support target tasks involving high-level planning and control strategies for manipulation, navigation, and interaction (Human Robot Interaction), a recent trend in robot intelligence research is to combine traditional data-driven approaches with the knowledge-driven approaches motivated by cognitive science and brain research. This extends the coverage of topics for this Special Issue from motor-level learning and trajectory control to semantic SLAM (Simultaneous Localization and Mapping) and scene understanding for intelligent control. We feel that the timing of this Special Issue is favorable given recent major achievements in the related research, such as the finding of brain GPS function in neuroscience and physiology and the high performance of state-of-the-art deep-learning-based recognition.

We encourage researchers in this field to contribute their original papers to share their technical achievements with the readers.

Prof. Tae-Yong Kuc
Prof. Minsung Kim
Guest Editors

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