Authors:
Dilek Arslan
and
Ferda N Alpaslan
Affiliation:
Middle East Technical University, Turkey
Keyword(s):
Behaviour hierarchy, behaviour-based robotics, neuro-fuzzy systems, autonomous navigation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Control
;
Fuzzy Systems
;
Hybrid Learning Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Neural Networks Based Control Systems
;
Soft Computing
Abstract:
In agent-based systems, especially in autonomous mobile robots, modelling the environment and its changes is a source of problems. It is not always possible to effectively model the uncertainty and the dynamic changes in complex, real-world domains. Control systems must be robust to changes and must be able to handle the uncertainties to overcome this problem. In this study, a reactive behaviour based agent control system is modelled and implemented. The control system is tested in a navigation task using an environment, which has randomly placed obstacles and a goal position to simulate an environment similar to an autonomous robot’s indoor environment. Then the control system was extended to control an agent in a multi-agent environment. The main motivation of this study is to design a control system, which is robust to errors and is easy to modify. Behaviour based approach with the advantages of fuzzy reasoning systems is used in the system.