PDDL4J: a planning domain description library for java

Abstract

Pddl4j (Planning Domain Description Library for Java) is an open source toolkit for Java cross-platform developers meant (1) to provide state-of-the-art planners based on the Pddl language, and (2) to facilitate research works on new planners. In this article, we present an overview of the Automated Planning concepts and languages. We present some planning systems and their most significant applications. Then, we detail the Pddl4j toolkit with an emphasis on the available informative structures, heuristics and search algorithms.

Social Human-Robot Interaction: A New Cognitive and Affective Interaction-Oriented Architecture

“…It is in charge of finding a way of achieving the selected intention according to a plan-based approach of dialogue [22]. It is based on the planning approach proposed by [21] and on the PDDL4J Java library [20]. The plans produced contain MCA and/or physical actions, whose preconditions and effects are formalised in the classical Planning Domain Description Language (PDDL), making most existing planners compatible with CAIO.…”

Primitive Action Based Combined Task and Motion Planning for the Service Robot

“…The simulator is V-REP, and the physical engine is Vortex. We implemented the task planner module using the pddl4j open library ( Pellier and Fiorino, 2018 ) for PDDL-based task planning in the task manager, and we calculated grasping force-closure and IK using moveit ( Chitta et al, 2012 ) and graspit ( Miller and Allen, 2004 ) for the implementation of motion plan modules in the behavior manager. All the modules of the proposed system are implemented in the Robot Operating System ( Quigley et al, 2009 ).…”

Software Architecture for Next-Generation AI Planning Systems

“…The basic approach towards the implementation of this service consists of converting internal data models into wrapped data models which are in turn serialised and provided as JSON The service implementation parses PDDL planning problems. This is accomplished using the PDDL4J library [64]. For other alternatives, see Section 8.…”

“…The encoding step transforms a given planning problem into its final form. Such a transformation is typical for most PDDL-based planners [64].…”

“…We wrap the whole data structure by custom classes to avoid serialisation problems. This implementation choice preserves the representation of a given planning problem as a causal domain transition graph, which provides an efficient way to determine which propositions are accessible from the current state [64].…”