Behavior-Based Systems

Traditional attempts at formulating complex control programs have been based on “Artificial Intelligence” (AI) theory. The dominant paradigm of this approach has been the sense-plan-act (SPA) organization: a mapping from perception, through construction of an internal world model, planning a course of action based upon this model, and finally execution of the plan in the real-world environment. Aspects of this method of robot control have been criticized, notably the emphasis placed on construction of a world model and planning actions based on this model [Agre, Chapman 1990], [Brooks 1986]. The computation time required to construct a symbolic model has a significant impact on the performance of the robot. Furthermore, disparity between the planning model and the actual environment may result in actions of the robot not producing the intended effect.

An alternative to this approach is described by behavior-based robotics. Reactive systems that do not use symbolic representation are demonstrably capable of producing reasonably complex behavior [Braitenberg 1984], see Section 1.1. Behavior-based robotic schemes extend the concept of simple reactive systems to combining simple concurrent behaviors working together.