Mixed-Initiative Interaction and Robotic Systems

A truly collaborative human-robot interaction framework should allow the participating agents to assume and relinquish initiative depending upon their own capabilities and their understanding of the environment. The goal of this work is to define and develop a mixed-initiative human– robot collaborative architecture in which affect-based sensing plays a critical role in initiative switching. Affectbased sensing implies that the robot detects the human’s emotional state in order to determine which actions to pursue. We have conducted an extensive literature review of Mixed-Initiative Interaction that has provided a basis for our architectural development. In particular, we are applying Riley’s (Riley 1989) general model of mixed-initiative interaction to our architecture development. We have developed a preliminary architecture and are now collecting affect-based participant data that will be used to test the system. The purpose of this paper is to provide an overview of Riley’s model, its application in our development, present our preliminary architecture, and present the affect-based interaction constraints that affect the architecture

[1]  Carla H. Lagorio,et al.  Psychology , 1929, Nature.

[2]  Jaime R Carbonell,et al.  Mixed-initiative man-computer instructional dialogues , 1970 .

[3]  Victor A. Riley,et al.  A General Model of Mixed-Initiative Human-Machine Systems , 1989 .

[4]  C A Smith.  Dimensions of appraisal and physiological response in emotion. , 1989, Journal of personality and social psychology.

[5]  Victor Riley.  Human Factors Issues of Data Link: Application of a Systems Analysis , 1992 .

[6]  D. Cicchetti.  Emotion and Adaptation , 1993 .

[7]  Yuichiro Anzai.  Human-robot-computer interaction: a new paradigm of research in robotics , 1993, Adv. Robotics.

[8]  Steven W. Mitchell.  An Architecture for Real-Time Mixed Initiative Collaborative Planning , 1997 .

[9]  Robin Cohen,et al.  A Constraint Satisfaction Framework for Managing Mixed-Initiative Discourse , 1997 .

[10]  Dan Ryan,et al.  Traded Control with Autonomous Robots as Mixed Initiative Interaction , 1997 .

[11]  R. R. Penner,et al.  Facilitating human interactions in mixed initiative systems through dynamic interaction generation , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[12]  S. Guerlain,et al.  Integrated Task Representation for Indirect InteractionPosition , 1997 .

[13]  Michael K. Brown,et al.  Initiative in Collaborative Interactions m Its Cues and Effects , 1997 .

[14]  Daniela D'Aloisi.  Mixed-Initiative Aspects in an Agent-Based System , 1997 .

[15]  Jennifer Healey,et al.  Digital processing of affective signals , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[16]  D. Fox,et al.  Towards Personal Service Robots for the Elderly , 1999 .

[17]  Marti A. Hearst.  Trends & Controversies: Mixed-initiative interaction , 1999, IEEE Intell. Syst..

[18]  Robin Cohen,et al.  User modeling in the design of interactive interface agents , 1999 .

[19]  Robin R. Murphy,et al.  Mixed-initiative control of multiple hetrogeneous robots for urban search and rescue , 2000 .

[20]  James F. Allen,et al.  Integrating agent-based mixed-initiative control with an existing multi-agent planning system , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[21]  Kenneth Hugdahl,et al.  Cognition and the autonomic nervous system: Orienting, anticipation, and conditioning. , 2000 .

[22]  Benjamin Bell,et al.  Leveraging Task Models for Team Intent Inference , 2000 .

[23]  Stanley Peters,et al.  The WITAS multi-modal dialogue system I , 2001, INTERSPEECH.

[24]  Michael A. Goodrich,et al.  Experiments in adjustable autonomy , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[25]  E. Vesterinen,et al.  Affective Computing , 2009, Encyclopedia of Biometrics.

[26]  Tetsuo Sawaragi,et al.  Naturalistic Human-Robot Collaboration Mediated by Shared Communicational Modality in Teleoperation System , 2001, Active Media Technology.

[27]  Rob Sherwood,et al.  Autonomously generating operations sequences for a Mars rover using AI-based planning , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[28]  Gabriella Cincotti,et al.  Frequency decomposition and compounding of ultrasound medical images with wavelet packets , 2001, IEEE Transactions on Medical Imaging.

[29]  Naren Ramakrishnan,et al.  Mixed-initiative interaction = mixed computation , 2001, PEPM '02.

[30]  Donald D. Dudenhoeffer,et al.  Mixed-initiative control for remote characterization of hazardous environments , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[31]  Koichi Osuka,et al.  Development of human-machine interface in disaster-purposed search robot systems that serve as surrogates for human , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[32]  Candace L. Sidner,et al.  COLLAGEN: A Collaboration Manager for Software Interface Agents , 1998, User Modeling and User-Adapted Interaction.

[33]  James C. Lester,et al.  Lifelike Pedagogical Agents for Mixed-initiative Problem Solving in Constructivist Learning Environments , 2004, User Modeling and User-Adapted Interaction.

[34]  Nilanjan Sarkar,et al.  Anxiety detecting robotic system – towards implicit human-robot collaboration , 2004, Robotica.

[35]  Chris Mellish,et al.  Exploring Mixed-Initiative Dialogue Using Computer Dialogue Simulation , 2004, User Modeling and User-Adapted Interaction.

[36]  Curry I. Guinn,et al.  An Analysis of Initiative Selection in Collaborative Task-Oriented Discourse , 1998, User Modeling and User-Adapted Interaction.