GUEST EDITORS:

* Prof. Meng Joo, Bharath University, India
* Dr. Zhaojie Ju, University of Portsmouth, UK
* Prof. Iqbal H. Jebril, Al-Zaytoonah University of Jordan, Jordan

DESCRIPTION:

Mobile robots have become more common in commercial and industrial settings. Mobile robots have many potential applications in routine or dangerous tasks such as the delivery of supplies in hospitals, cleaning of offices, and operations in a nuclear plant. Operator interface, Mobility or locomotion, Manipulators & Effectors, Programming, Sensing & Perception are the five primary Areas of Robotics. Articulated, SCARA, Delta & Cartesian Robots form the major classification in robotics. The use of robots has more than doubled in the last 20 years in most advanced economies. The top users of industrial robots in 2017 were China, Japan, and South Korea, using nearly 50% of the world's stock of robots. Regarding industries, the highest usage of industrial robots in 2017 belonged to the automotive industry, which employed about 42% of all robots followed by the electrical and electronics industry at 28% approx. Onto the downsides of robots, they need oodles of electricity to run which lead to additional issues with global warming and greenhouse gas emissions. They rely on clever humans to program them for specific tasks. And, though artificial intelligence and machine learning are coming on fast, this is a limiting factor in what Robots can do. One of the fundamental and critical research areas in mobile robotics is navigation, which generally includes local navigation and global navigation. Local navigation learns or plans the local paths using the current sensory inputs without prior complete knowledge of the environment, whereas Global navigation learns or plans the global paths based on a relatively abstract and complete knowledge about the environment.
Hybrid learning algorithms for fuzzy neural network (FNN) systems, which combine back-propagating learning and genetic algorithms, are a good alternative for solving complex problems. Hybrid control architecture, which combines the advantage of both local and global optimization, and it has received considerable attention in the research area of mobile robotics. Although hybrid control is mostly adopted for robot navigation, the practical design and its performance, Behaviour design of robots, selection of learning, and control algorithms for robot navigation systems are the major challenges in research areas.

The topics of interest for this Special Issue include, but are not limited to:
- Hybrid approach for autonomous robot navigation system
- Hybrid fuzzy controller for real-time mobile robot navigation
- Fuzzy logic controller for intelligent robots
- Application of fuzzy logic and image processing for mobile robot assistance
- Hybrid fuzzy based collision avoidance for a mobile robot
- Hybrid fuzzy systems for the development of a re-engagement system for socially interactive robots

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