Attentional Plan Execution for Human-Robot Cooperation Jonathan Cacace 1 , Riccardo Caccavale 1 , Michelangelo Fiore 2 , Rachid Alam` ı 2 , and Alberto Finzi 1 1 Universit` a degli Studi di Napoli Federico II {jonathan.cacace,riccardo.caccavale,alberto.finzi}@unina.it 2 LAAS-CNRS {mfiore,rachid.alami}@laas.fr Abstract. In human-robot interactive scenarios communication and col- laboration during task execution are crucial issues. Since the human be- havior is unpredictable and ambiguous, an interactive robotic system is to continuously interpret intentions and goals adapting its executive and communicative processes according to the users behaviors. In this work, we propose an integrated system that exploits attentional mechanisms to flexibly adapt planning and executive processes to the multimodal human-robot interaction. 1 Introduction In social robotics, flexible and natural interaction with humans is often needed in the context of structured collaborative tasks. In these scenarios, the robotic system should be capable of adapting the execution of cooperative plans with respect to complex human activities and interventions. Many mechanisms are indeed involved in humans cooperation [3], such as joint attention, action ob- servation, task-sharing, and action coordination [19,15]. Furthermore, commu- nication between humans involve different modalities such as speech, gaze ori- entation, gestures [4]. Several systems manage the human-robot cooperation by planning (totally or partially) the action sequence for the agents involved in the interaction [11, 12, 20]; however, planning and replanning processes can be time- expensive and can therefore impair the naturalness and the effectiveness of the interaction. In order to flexibly combine and orchestrate structured activities and reactive actions we exploit the concept of cognitive control proposed by the cog- nitive neuroscience literature [17, 2]. Inspired by supervisory attentional system and contention scheduling models [17, 9, 2], we propose an integrated framework that combines planning, attentional regulations, and multimodal human-robot interaction in order to flexibly adapt plan execution according to the executive context and the multimodal intraction processes. 2 System Architecture In Fig. 1, we illustrate the overall architecture of the human-robot interaction system, the main components are described below.