FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning

Abstract

Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency.FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments.

Enhancing awareness of industrial robots in collaborative manufacturing

“…Such plans are generally seen as sequences of actions to be executed starting from an initial state. Several planning formalisms exist in literature each supporting different reasoning capabilities e.g., causal reasoning [36,45,60], numeric and temporal reasoning [26,39] or hierarchical reasoning [10,64]. HRC requires reasoning on the simultaneous execution of human and robot actions, taking into account different qualities of the resulting collaborative processes e.g., cycle time, safety, and idle time of the robot.…”

“…9 The reasoning mechanisms and the knowledge extraction procedure of Algorithm 1 have been developed in Java using Apache Jena. 10 Representation and reasoning functionalities have been integrated into ROS 11 through Fig. 6.…”

“…. , cell (5,10)) represents a specific destination of a PickPlace function, moving a specific WorkPiece. The human and the robot can thus perform the same type of Function i.e., PickPlace.…”