AND/OR net representation for robotic task sequence planning

Abstract

The paper describes a framework for task sequence planning for a generalized robotic work cell. The AND/OR net provides a compact, distributed, domain-specific representation of geometric configurations of parts and devices in the work cell. The approach maintains a correspondence from geometric state information to task and motion plans and on-line discrete-event control that is not available in traditional action-based planners. The feasibility criteria for each AND/OR net transition guide the geometric reasoning required in the planning of feasible sequences. The resulting search space for plans is often much smaller (due to explicit representation of geometric constraints) than the state space of an action-based task planner. For purposes of analysis, the AND/OR net is mapped into a Petri net and the resulting Petri net is shown to be bounded and have guaranteed properties of liveness, safeness, and reversibility. In this form, the AND/OR net may be viewed as a Petri net synthesis tool in which the resulting Petri net representation may be used for on-line scheduling and control of the system.