Abstract

Many of today?s robotic work cells are unable to adapt to even small changes in tasking without significant reprogramming. This results in downtime for production lines anytime a change to a product or procedure must be made. This paper examines a novel knowledge-driven system that provides added agility by removing the programming burden for new activities from the robot and placing it in the knowledge representation. The system is able to automatically recognize and adapt to changes in its work-flow and dynamically change assignment details. The system also provides for action verification and late binding of action parameters, thus providing flexibility by allowing plans to adapt to production errors and changing environmental conditions. The key feature of this system is its knowledge base that contains the necessary relationships and representations to allow for adaptation. This paper presents the ontology that stores this knowledge as well as the overall system architecture. The manufacturing domain of kit construction is examined as a sample test environment. HighlightsWe examine a novel knowledge-driven system that provides added agility.System removes the programming burden for new activities from the robot.System provides for action verification and late binding of action parameters.System adapts to production errors and changing environmental conditions.We present our ontology as well as the overall system architecture.

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.