Autonomous mobile robots navigating in changing and dynamic unstructured environments
like the outdoor environments need to cope with large amounts of uncertainties that are …

This paper proposes an evolutionary-group-based particle-swarm-optimization (EGPSO)
algorithm for fuzzy-controller (FC) design. The EGPSO uses a group-based framework to …

This paper proposes an obstacle avoidance method in the position stabilization of the
wheeled mobile robots using interval type-2 fuzzy neural network (IT2FNN). Previously, we …

An approach to the problem of autonomous mobile robot obstacle avoidance using
reinforcement learning neural network is proposed in this paper. Q-learning is one kind of …

The design of fuzzy controllers for the implementation of behaviors in mobile robotics is a
complex and highly time-consuming task. The use of machine learning techniques, such as …

The ability to reliably detect faults is essential in many real-world tasks that robot swarms
have the potential to perform. Most studies on fault detection in swarm robotics have been …

Singleton interval type-2 fuzzy logic systems (FLSs) have been widely applied in several
real-world applications, where it was shown that the singleton interval type-2 FLSs …

The type-2 Fuzzy Logic Controller (FLC) has started to emerge as a promising control
mechanism for autonomous mobile robots navigating in real world environments. This is …

This paper presents a methodology for the design of fuzzy controllers with good
interpretability in mobile robotics. It is composed of a technique to automatically generate a …

Some autonomous navigation methods, when implemented alone, can lead to poor
performance, whereas their combinations, when well thought out, can yield exceptional …