Abstract
In this study, Fuzzy Logic (FL) and Interval Type-2 FL (IT-2FL) controllers were applied to a mobile robot in order to determine which method facilitates navigation and enables the robot to overcome real-world uncertainties and track an optimal trajectory in a very short time. The robot under consideration is a non-holonomic unicycle mobile robot, represented by a kinematic model, evolving in two different environments. The first environment is barrier-free, and moving the robot from an initial to a target position requires the introduction of a single action module. Subsequently, the same problem was approached in an environment closer to reality, with objects hindering the robot's movement. This case requires another controller, called obstacle avoidance. This system allows the robot to reach autonomously a well-defined target by avoiding collision with obstacles. The robustness of the structures of the defined controllers is tested in Matlab simulations of the studied controllers. The results show that the IT-2FL controller performs better than the FL controller.
Highlights
A mobile robot is generally equipped with perception and decision-making capabilities and actions that allow it to navigate safely and successfully in a given environment and to follow a desired trajectory
The main challenge regarding mobile robots is the development of intelligent navigation systems [3]
The generalized coordinates of the system are given by q = [ x, y,θ, φ r,φ l ]T where [x, y] are the Cartesian coordinates of the mobile robot, θ is its orientation measured from the x-axis and φr,φl are the angular positions of the right and left wheel respectively [2, 3]
Summary
A mobile robot is generally equipped with perception and decision-making capabilities and actions that allow it to navigate safely and successfully in a given environment and to follow a desired trajectory. This objective is achieved without or with a reduced human intervention [1]. The developments of sensors, microprocessors, and control technology have enabled mobile robots to perform very complex tasks. The main problem of navigation of mobile robots can be broken down into three sub-problems: reaching the target, avoiding obstacles, and tracking an optimal trajectory in a very short time. The robot under consideration is a non-holonomic unicycle mobile robot, represented by a kinematic model
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
