Computational intelligence (CI) focuses on the theory, design, application, and development of biologically and linguistically motivated computational paradigms combining elements of learning, adaptation, evolution and fuzzy logic.

Computational intelligence originally developed as a branch of artificial intelligence but now it has a large enough extent to be recognized as a separate domain of research. In general, typical artificial intelligence techniques are top-to-bottom where, i.e., the structure of models, solutions, etc. is imposed from above. Computational intelligence techniques are generally bottom-up, where order and structure emerges from an unstructured beginning.

The areas covered by the term computational intelligence include: neural networks, connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, swarm intelligence, artificial immune systems and hybrid intelligent systems in which these paradigms are contained.

Computational intelligence is also closely related to soft computing, which indicates the difference from operations research, also known as hard computing. With similar problem domains, soft computing puts no conditions on the problem but also provides no guarantees for success, a deficiency which is compensated by the robustness of the methods.

Control is an interdisciplinary branch of engineering and mathematics dealing with the design, identification and analysis to provide specific tasks system desired performance. In the earlier time, system control mainly focused on automatic regulation used in industrial control based on the concept of feedback. Based on transfer function, classical control theory has been later been developed for single-input-single-output and linear time-invariant systems. With the rapid advancements in applied mathematics and computer science, control theory entered the modern control era in 1970’s to handle multi-input-multi-output and time-varying systems with high performance and precision. In the last decade, control continues to advance rapidly to intelligent control, distributed control, etc. when new understandings and new technologies emerge.

Nowadays, control engineering is using control theories and advanced technologies to develop more sophisticated and reliable controllers with a wide range of applications from the flight and propulsion systems of commercial airliners, to the cruise control present in many modern automobiles, to tele-operations, and to real-time internet-based distributed control. It has permeated into every single part of our lives and will continues to play an important role in our societies.

Mechatronics is a multi-disciplinary area incorporating mechanical systems, electronics, and control theory for the design of products and control processes. It relates to the design of systems, devices and products aimed at achieving an optimal balance between basic mechanical structure and its overall control. A few examples of mechatronics systems are cruise control in a car, autofocus in camera, robot controllers, manufacturing plants automation, car assembly, autopilot system etc.

The latest research trend in Mechatronics focuses on efficient, fast, multi-component (sensors and actuators) modular/scalable system design. Real-time large-scale mechatronics systems coordinated over networks is another thrust. The challenge is integrating enough intelligence in a real-world system; where size and cost are the primary constraints.

Mechatronics will fuel technologies advancements such as intelligent space, robotic rooms, remote surgeries, autonomous vehicles, physical-cyber space integration transportation systems, distributed generation systems.

“A robot is a machine that gathers information about its environment and uses that information to follow instructions to do some sort of work.” (The Tech Museum of Innovation, 2000) The robot sensory system gathers specific information needed by the control system. The robot control system directs the motion and sensory processing of a robot. The robots mechanical system then produces motion that results in manipulation or locomotion.

Robotics is the science and engineering concerned with the design, manufacture and application of robots, and computer systems for their control, sensory feedback, and information processing. The many types of robotic systems include robotic manipulators, robotic hands, mobile robots, walking robots, aids for disabled persons, tele-robots, and microelectro-mechanical systems. Robotics Engineers study electronics, computer science, artificial intelligence, mechatronics, nanotechnology, and bioengineering.