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Towards Robust Assembly with Knowledge Representation for the Planning Domain Definition Language (PDDL)



Zeid Kootbally, Craig I. Schlenoff, Christopher R. Lawler, Thomas R. Kramer, Satyandra K. Gupta


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.
Robotics and Computer-Integrated Manufacturing


PDDL (Planning Domain Definition Language), planning, replanning, plan repair, agility, OWL (Web Ontology Language), knowledge representation, robotics, XSDL (XML Schema Definition Language)


Kootbally, Z. , Schlenoff, C. , Lawler, C. , Kramer, T. and Gupta, S. (2014), Towards Robust Assembly with Knowledge Representation for the Planning Domain Definition Language (PDDL), Robotics and Computer-Integrated Manufacturing, [online], (Accessed April 25, 2024)
Created September 10, 2014, Updated November 10, 2018