Decision-Making Mechanism to Organize the Agenda of a Guide-Robot

One of the major challenges in evolutionary robotics is constituted by the need of the robot being able to make decisions on its own, in accordance with the multiple tasks programmed, optimizing its timings and power. In this paper, we present a new automatic decision making mechanism for a robot guide that allows the robot to make the best choice in order to reach its aims, performing its tasks in an optimal way. The election of which is the best alternative is based on a series of criteria and restrictions of the tasks to perform. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality in the decision making. The modeling of the quality index of the best choice to perform is made using fuzzy logic and it represents the beliefs of the robot, which continue to evolve in order to match the "external reality”. This fuzzy system is used to select the most appropriate set of tasks to perform during the day. With this tool, the tour guide-robot prepares its agenda daily, which satisfies the objectives and restrictions, and it identifies the best task to perform at each moment. This work is part of the ARABOT project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide.