Two broad classes of robot controllers are the modular, and the model based approaches. The modular approaches include the Reactive or Behavior Based designs. They do not rely on mathematical system models, but are easy to design, modify and extend. In the model based approaches, a model is used to design a single controller with verifiable system properties. The resulting designs are however often hard to extend, without jeopardizing the previously proven properties. This paper describes an attempt to narrow the gap between the flexibility of the modular approaches, and the predictability of the model based approaches, by proposing a modular design that does the combination, or arbitration, of the different modules in a model based way. By taking the (model based) time derivatives of scalar, Lyapunov-like, objective functions into account, the arbitration module can keep track of the time evolution of the objectives. This enables it to handle objective tradeoffs in a predictable way by finding controls that preserve an important objective that is currently met, while striving to satisfy another, less important one that is not yet achieved. To illustrate the approach a UAV control problem from the literature is solved, resulting in comparable, or better, performance.
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