Towards robust assembly with knowledge representation for the planning domain definition language (PDDL). (June 2015)

• Record Type: Journal Article
• Authors: Kootbally, Z.; Schlenoff, C.; Lawler, C.; Kramer, T.; Gupta, S.K.
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 33(2015)
• Page Start: 42
• Page End: 55
• Publication Date: 2015-06
• Subjects: PDDL (Planning Domain Definition Language) -- Planning -- Replanning -- Agility -- Knowledge representation -- Robotics; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2014.08.006
• Languages: English
• ISSNs: 0736-5845

Abstract

Abstract: The effort described in this paper attempts to integrate agility aspects in the "Agility Performance of Robotic Systems" (APRS) project, developed at the National Institute of Standards and Technology (NIST). The new technical idea for the APRS project is to develop the measurement science in the form of an integrated agility framework enabling manufacturers to assess and assure the agility performance of their robot systems. This framework includes robot agility performance metrics, information models, test methods, and protocols. This paper presents models for the Planning Domain Definition Language (PDDL), used within the APRS project. PDDL is an attempt to standardize Artificial Intelligence planning languages. The described models have been fully defined in the XML Schema Definition Language (XSDL) and in the Web Ontology Language (OWL) for kit building applications. Kit building or kitting is a process that brings parts that will be used in assembly operations together in a kit and then moves the kit to the area where the parts are used in the final assembly. Furthermore, the paper discusses a tool that is capable of automatically and dynamically generating PDDL files from the models in order to generate a plan or to replan from scratch. Finally, the ability of the tool to update a PDDL problem file from a relational database for replanning to recover from failures is presented. Abstract : Highlights: Models for PDDL structure. Tool for automatic and dynamic generation of PDDL files. Tool for update of PDDL problem file from a dynamic relational database. Knowledge methodology/model allows agility, flexibility, and rapid re-tasking during failures.