Modelling human gameplay at pool and countering it with an anthropomorphic robot

Abstract

Interaction between robotic systems and humans becomes increasingly important in industry, the private and the public sector. A robot which plays pool against a human opponent involves challenges most human robot interaction scenarios have in common: planning in a hybrid state space, numerous uncertainties and a human counterpart with a different visual perception system. In most situations it is important that the robot predicts human decisions to react appropriately. In the following, an approach to model and counter the behavior of human pool players is described. The resulting model allows to predict the stroke a human chooses to perform as well as the outcome of that stroke. This model is combined with a probabilistic search algorithm and implemented to an anthropomorphic robot. By means of this approach the robot is able to defeat a player with better manipulation skills. Furthermore it is outlined how this approach can be applied to other non-deterministic games or to tasks in a continuous state space. © Springer International Publishing 2013.