REPRESENTING AND ANALYZING ACTION PLANS AS NETWORKS OF CONCURRENT PROCESSES

Constructing action plans for a robot operating in an environment cont aining uncertain and dynamic events is a difficult task. Indeed, the i nadequacy of the standard approaches for representing and producing pl ans for such environments has led some researchers to abandon explicit plan representation and to directly program behavior instead. Ultimat ely, no matter which approach is taken, producing appropriate behavior in such environments requires writing robot programs or action plans that include conditionals, loops, requests for sensory data, concurren cy, etc. Existing approachs are simply not adequate to the task of mod eling and analyzing such plans. Nonetheless, it is necessary that such plans be open to formal analysis: the complexity of control necessary to operate in uncertain and dynamic environments demands that more th an human intuition be used to verify, or preferably autogenerate, such plans. The problem of constructing a plan representation that can dea l with the complexity of representing and analyzing robot behavior in uncertain and dynamic environments is addressed. The key contributions are as follows. A concurrent-process based representation is develope d which represents both the plan (or controller) and the uncertain and dynamic environment in which the plan operates. A methodology is outl ined for analyzing the behavior of this interacting system of plan and world. This methodology is illustrated with a mixed-batch example fro m the domain of robotic kitting. To balance the theoretical work, a de scription of the implemented robot kitting cell is presented.