Abstract

In order to obtain more effective coordinated behaviors against changes in environments or unlearned environments, we here propose a new fusion unit using external sensor information for a fuzzy behavior-based control system trained in the framework of module learning. The present fusion unit falls into a class of adaptive priority-based architecture in which the fusion between behavioral elements is carried out by a cooperation or comnetition strategy, depending on whether an objective point or obstacle can be detected or not. Some experimental results of a miniature mobile robot Khepera show that the proposed metcod is superior to the conventional method that applies a fusion unit based on a fixed priority-based architecture.

Full Text
Paper version not known

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

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.