TITLE:
The Proposed Fuzzy_IAMR Approach
AUTHORS:
Ouarda Hachour
KEYWORDS:
Intelligent Autonomous Mobile Robot (IAMR); Expert System; Fuzzy Logic (FL); Navigation
JOURNAL NAME:
Positioning,
Vol.4 No.1,
February
28,
2013
ABSTRACT: In this paper we present a fuzzy_IAMR
Intelligent Autonomous Mobile Robot navigation approach of Autonomous Mobile
Robot. The robot has to find a collision-free trajectory between the starting
configuration and the goal configuration in a static unknown environment containing some obstacles. To deal
with autonomy requirements and to present a real intelligent task, the use of
the Fuzzy Logic FL has an advantage of adaptivity such that this approach works
perfectly even if an
environment is unknown. In this context, we present a software implementation
Fuzzy Logic FL path planning in a terrain. Fuzzy logic allows a continuum of
control variables such as heading angles and speeds to be considered, as opposed to the discrete
numbers used in crisp behaviors. Artificial intelligence, including Fuzzy logic
has been actively studied and applied to domains such as automatically control
of complex systems like robot. In f act, recognition, learning, decision-making, and
action constitute the principal obstacle avoidance problems, so it is interesting
to replace the classical approaches by technical approaches based on
intelligent computing technologies. This technology FL is becoming useful as alternate
approach to the classical techniques one. Also, fuzzy logic can be viewed as an
attempt to bring together conventional precise mathematics and humanlike
decision-making concepts. Fuzzy logic can be a valid approach solving control
problem in a wide range of applications. To deal with the principle, the robot
moves within the unknown environment by sensing and avoiding the obstacles
coming across its way towards the unknown target. This algorithm provides the
robot the possibility to move from the initial position to the final position
(target) without collisions where the main factors of moving are included such
as learning, deciding, acting, cognition, perception, and thinking. The robot succeeds
to reach the target without collisions. The results gotten of the FL on randomly
generated terrains are very satisfactory and promising. The extension of the FL
for solving both paths planning and trajectory planning.