ROBOT BEHAVIOR COORDINATION BASED ON FUZZY DECISION-MAKING

This paper introduces a fuzzy decision-making algorithm for robot behavior coordination. The algorithm belongs to the arbitration class of behavior coordination mechanisms, under which only one behavior is running at a time. However, it is possible to use a hierarchical decision mechanism for hierarchical behaviors without interference between hierarchical levels. With this fuzzy decision method it is possible to represent a specific model of the world where the robot evolves. This algorithm consists of defining a set of behaviors, a set of world states, a cost function for behaviors, a set of goals, and a set of constraints. For each behavior and actual world state pair, a cost function is computed. The cost of each pair is evaluated by the overall goals. Goals and constraints are aggregated using a fuzzy operator and the optimal choice is the behavior with the maximum resulting value. This algorithm was tested with success in realistic simulations of a goalkeeper soccer robot.