| Abstract: | The importance of solving the problem of integrating deliberative (“planning”) capabilities and reactive capabilities when building robust, ‘real-world’ robot systems is becoming widely accepted (Bresina and Drummond, 1990; Fraichard and Laugier, 1991; McDermott, 1991). This paper presents a solution to this problem: cast planning as the incremental adaptation of a reactive system to suit changes in goals or the environment. Our application domain is a manufacturing problem - robotic kitting. This paper represents an advance on existing work in two ways: It presents and formally examines an architecture that incorporates the benefits of a deliberative component without compromising the reactive component. Secondly, it provides the first set of performance statistics in the literature for this class of system. In our approach, the reactive system (the reactor) is a real-time system that continually interacts with the environment, and the planner is a separate and concurrent system that incrementally ‘tunes’ the behavior of the reactor to ensure that goals are achieved. We call this the planner-reactor approach. The reactor is described using a formal framework for representing flexible robot plans, the model (Lyons, 1990; Lyons and Arbib, 1989). Thus, the behavior of the reactor, and the rules by which the reactor can be modified, become open to mathematical analysis. We employ this to determine the constraints the planner must abide by to make safe adaptations and to ensure that incremental adaptations converge to a desired reactor. We discuss our current implementation of planner and reactor, work through an example from the kitting robot application, and present implementation results. |
