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Improvement of group performance of job distributed mobile robots by an emotionally biased control system

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Abstract

This paper deals with the implementation of emotions in mobile robots performing a specified task in a group in order to develop intelligent behavior and easier forms of communication. The overall group performance depends on the individual performance, group communication, and the synchronization of cooperation. With their emotional capability, each robot can distinguish the changed environment, can understand a colleague robot’s state, and can adapt and react with a changed world. The adaptive behavior of a robot is derived from the dominating emotion in an intelligent manner. In our control architecture, emotion plays a role to select the control precedence among alternatives such as behavior modes, cooperation plans, and goals. Emotional interaction happens among the robots, and a robot is biased by the emotional state of a colleague robot in performing a task. Here, emotional control is used for a better understanding of the colleague’s internal state, for faster communication, and for better performance eliminating dead time.

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References

  1. Picard RW (2000) Affective computing, paperback edn. First MIT Press, Cambridge

    Google Scholar 

  2. Damasio AR (1994) Descartes’ error: emotion, reason, and the human brain. Putnam, New York

    Google Scholar 

  3. Katzenbach J, Smith DK (1994) The wisdom of teams. Harper Business, New York

    Google Scholar 

  4. Jennings J (1990) The teamwork: united in victory. Silver Burdett Press, Englewood Cliffs

    Google Scholar 

  5. Nair R, Tambe M, Marsella S (2005) The role of emotions in multiagent teamwork: a preliminary investigation. In: Fellous J-M, Arbib M (eds) Who needs emotions: the brain meets the robot. Oxford University Press, Oxford

    Google Scholar 

  6. Breazeal C, Scassellati B (2000) Infant-like social interactions between a robot and a human caretaker. Adaptive Behav 8:47–72

    Article  Google Scholar 

  7. Velásquez JD (1998) A computational framework for emotion-based control. Workshop on Grounding Emotion in Adaptive System, 5th International Conference of the Society for Adaptive Behavior (SAB’98), Aug. 21, Zurich, Switzerland, pp 62–67

  8. Shibata T, Ohkawa K, Tanie T (1996) Spontaneous behavior of robots for cooperation of emotionally intelligent robot system. IEEE Proceedings of the International Conference on Robotics and Automation 3, Apr. 22–28, Minneapolis, MN, USA, pp 2426–2431

  9. Mataric MJ, Nilson M, Simsarian KT (1995) Cooperative multi-robot box-pushing. Proceedings of IROS, Pittsburgh, PA, USA, Aug. 5–9, pp 556–561

  10. Parker L (1998) Alliance: an architecture for fault-tolerant multirobot cooperation. IEEE Trans Robotics Autom 14:220–240

    Article  Google Scholar 

  11. Schneider-Fontan M, Mataric M (1998) Territorial multi-robot task division. IEEE Trans Robotics Autom 14:815–822

    Article  Google Scholar 

  12. Murphy RR, Lisetti CL, Tardif R, et al. (2002) Emotion-based control of cooperating heterogeneous mobile robots. IEEE Trans Robotics Autom 18:744–757

    Article  Google Scholar 

  13. Arun C (1997) A computational architecture to model human emotions. Proceedings of the International Conference on Intelligent Information System, Dec. 8–10, Grand Bahama Island, Bahamas, pp 86–89

  14. Daneshvar R, Lucas C (2003) Improving reinforcement learning algorithm using emotions in multi-agent system. Lecture Notes in Artificial Intelligence 2792, Springer, Berlin, Germany, pp 361–362

    Google Scholar 

  15. Oatley K (1992) Best laid schemes: the psychology of emotions. Cambridge University Press, Cambridge

    Google Scholar 

  16. Bates J (1994) The role of emotion in believable agents. Commun ACM 31(7):122–125

    Article  Google Scholar 

  17. Margulies A (1993) Empathy, virtuality, and the birth of complex emotional states: do we find or do we create feelings in the other. In: Albon SL, Brown D, Khantzian EJ, et al. (eds) Human feelings: explorations in affect development and meaning. Analytic Press, Hillsdale, NJ, London

    Google Scholar 

  18. Kolja K, Martin B (2004) Towards an emotion core based on a hidden Markov model. 13th IEEE International Workshop on Robot and Human Interactive Communication, Sep. 20–22, Kurashiki, Okayama, Japan, pp 119–124

  19. Trivedi KS (1982) Probability and statistics with reliability, queuing, and computer science application. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  20. Theodor S (2001) KiKS is a Khepera simulator. Master Thesis, Umeå University, Sweden

    Google Scholar 

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Correspondence to Keigo Watanabe.

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Banik, S.C., Watanabe, K. & Izumi, K. Improvement of group performance of job distributed mobile robots by an emotionally biased control system. Artif Life Robotics 12, 245–249 (2008). https://doi.org/10.1007/s10015-007-0476-2

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  • DOI: https://doi.org/10.1007/s10015-007-0476-2

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