Jian Chu; Rob Buckingham; Max Meng, Editors-in-Chief, IET Cyber-Systems & Robotics
We are honored to serve the inaugural Editors-in-Chief of the new journal, IET Cyber-Systems & Robotics.
In the year of 1948, Norbert Wiener published the famous book “Cybernetics: or Control and Communication in the Animal and the Machine” which defines cybernetics as a cutting-edge discipline of synergic studies between control and communication in both animals and machines. In the 1950s, cybernetics was more like a philosophical concept rather than an easily available technology of that moment. With the rapid progress in many areas such as automatic control, artificial intelligence, neuroscience, and communication within the past decades, nowadays the magnificent picture sketched by Wiener in his “Cybernetics” book is becoming a reality. Among uncountable examples, brain-computer interface (BCI) is really the most exciting representative of cybernetics, where bi-directional information flow exists between the bio-minds and manmade machines.
Now, it is our great pleasure to welcome you to the very first issue of IET Cyber-Systems & Robotics. From this issue, you will read the history and recent progress of the aerodynamic mechanisms in bio-inspired micro air vehicles (MAVs) [1]; a survey of the state-of-the-art algorithms of optimal motion planning [2]; a method of flow field inference based on image sequence data and PDE model [3]; a novel reinforcement learning (RL) framework involving traditional cybernetics [4]; and a policy-search-based method for efficient thrust generation of robotic fish caudal fins [5].
We expect IET Cyber-Systems & Robotics to become a unique journal on promoting multidisciplinary research of cybernetics and robotics, to reflect the most recent evolution of Wiener’s “Cybernetics” in an information-rich world.
With the effort and contribution from researchers around the world, we believe that IET CyberSystems & Robotics journal has a high possibility of becoming an exciting forum for unbounded technological innovations on any cybernetic systems and robotics.
[2] A survey of optimal motion planning
[3] Visual inference of flow flux via free surface PDE model and image sequence assimilation
[4] Time-in-Action Reinforcement Learning
[5] Efficient thrust generation in robotic fish caudal fins using policy search