Authors:
Abdelkarim Souissi
and
Hacene Rezine
Affiliation:
EMP, Algeria
Keyword(s):
Mobile Robot Navigation, Reactive Navigation, Fuzzy Control, Reinforcement learning, Fuzzy Actor Critic Learning.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Control
;
Fuzzy Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Mobile Robots and Autonomous Systems
;
Optimization Algorithms
;
Reasoning about Action for Intelligent Robots
;
Robotics and Automation
;
Soft Computing
Abstract:
In this article, we are interested in the reactive behaviours navigation training of a mobile robot in an unknown environment. The method we will suggest ensures navigation in unknown environments with presence off different obstacles shape and consists in bringing the robot in a goal position, avoiding obstacles and releasing it from the tight corners and deadlock obstacles shape. In this framework, we use the reinforcement learning algorithm called Fuzzy Actor-Critic learning, based on temporal difference prediction method. The application was tested in our experimental PIONEER II platform.