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Human-Robot Collaborative Navigation Search Using Social Reward Sources

  • Marc DalmassoEmail author
  • Anaís Garrell
  • Pablo Jiménez
  • Alberto Sanfeliu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1093)

Abstract

This paper proposes a Social Reward Sources (SRS) design for a Human-Robot Collaborative Navigation (HRCN) task: human-robot collaborative search. It is a flexible approach capable of handling the collaborative task, human-robot interaction and environment restrictions, all integrated on a common environment. We modelled task rewards based on unexplored area observability and isolation and evaluated the model through different levels of human-robot communication. The models are validated through quantitative evaluation against both agents’ individual performance and qualitative surveying of participants’ perception. After that, the three proposed communication levels are compared against each other using the previous metrics.

Keywords

Human-robot interaction Human-robot collaboration Human-Robot Collaborative Navigation Social reward Motion planning 

Notes

Acknowledgements

Work supported under projects ColRobTransp (DPI2016-78957-RAEI/FEDER EU), TERRINet (H2020-INFRAIA-2017-1-two-stage-730994) and by the Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI (MDM-2016-0656).

References

  1. 1.
    Ajoudani, A., Zanchettin, A.M., Ivaldi, S., Albu-Schäffer, A., Kosuge, K., Khatib, O.: Progress and prospects of the human-robot collaboration. Auton. Robots 42, 957–975 (2018)CrossRefGoogle Scholar
  2. 2.
    Andersen, R.S., Madsen, O., Moeslund, T.B., Amor, H.B.: Projecting robot intentions into human environments. In: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 294–301. IEEE (2016)Google Scholar
  3. 3.
    Brambilla, M., Ferrante, E., Birattari, M., Dorigo, M.: Swarm robotics: a review from the swarm engineering perspective. Swarm Intell. 7(1), 1–41 (2013)CrossRefGoogle Scholar
  4. 4.
    Bratman, M.E.: Shared cooperative activity. Philos. Rev. 101(2), 327–341 (1992)CrossRefGoogle Scholar
  5. 5.
    Carlson, T., Demiris, Y.: Collaborative control for a robotic wheelchair: evaluation of performance, attention, and workload. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 42(3), 876–888 (2012)CrossRefGoogle Scholar
  6. 6.
    Chen, M., Nikolaidis, S., Soh, H., Hsu, D., Srinivasa, S.: Planning with trust for human-robot collaboration. In: Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 307–315. ACM (2018)Google Scholar
  7. 7.
    Clark, H.H., Schreuder, R., Buttrick, S.: Common ground at the understanding of demonstrative reference. J. Verbal Learn. Verbal Behav. 22(2), 245–258 (1983)CrossRefGoogle Scholar
  8. 8.
    Clodic, A., Pacherie, E., Alami, R., Chatila, R.: Key elements for human-robot joint action. In: Sociality and Normativity for Robots, pp. 159–177. Springer (2017)Google Scholar
  9. 9.
    Devin, S., Alami, R.: An implemented theory of mind to improve human-robot shared plans execution. In: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 319–326. IEEE (2016)Google Scholar
  10. 10.
    Dragan, A.D., Bauman, S., Forlizzi, J., Srinivasa, S.S.: Effects of robot motion on human-robot collaboration. In: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, pp. 51–58. ACM (2015)Google Scholar
  11. 11.
    Ferrer, G., Zulueta, A.G., Cotarelo, F.H., Sanfeliu, A.: Robot social-aware navigation framework to accompany people walking side-by-side. Auton. Robots 41(4), 775–793 (2017)CrossRefGoogle Scholar
  12. 12.
    Fong, T., Thorpe, C., Baur, C.: Collaboration, dialogue, human-robot interaction. In: Robotics Research, pp. 255–266. Springer (2003)Google Scholar
  13. 13.
    Garrell, A., Garza-Elizondo, L., Villamizar, M., Herrero, F., Sanfeliu, A.: Aerial social force model: a new framework to accompany people using autonomous flying robots. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017, Vancouver, BC, Canada, 24–28 September 2017, pp. 7011–7017 (2017)Google Scholar
  14. 14.
    Hoffman, G.: Evaluating fluency in human-robot collaboration. IEEE Trans. Hum.-Mach. Syst. 49, 209–218 (2019)CrossRefGoogle Scholar
  15. 15.
    Hoffman, G., Breazeal, C.: Collaboration in human-robot teams. In: AIAA 1st Intelligent Systems Technical Conference, p. 6434 (2004)Google Scholar
  16. 16.
    Hommel, B., Müsseler, J., Aschersleben, G., Prinz, W.: The theory of event coding (TEC): a framework for perception and action planning. Behav. Brain Sci. 24(5), 849–878 (2001)CrossRefGoogle Scholar
  17. 17.
    Jackson, D.E., Ratnieks, F.L.: Communication in ants. Curr. Biol. 16(15), R570–R574 (2006)CrossRefGoogle Scholar
  18. 18.
    Jayawardena, C., Ardekani, I., et al.: A navigation model for side-by-side robotic wheelchairs for optimizing social comfort in crossing situations. Robot. Auton. Syst. 100, 27–40 (2018)CrossRefGoogle Scholar
  19. 19.
    Lemaignan, S., Warnier, M., Sisbot, E.A., Clodic, A., Alami, R.: Artificial cognition for social human-robot interaction: an implementation. Artif. Intell. 247, 45–69 (2017)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Morales, Y., Kanda, T., Hagita, N.: Walking together: side-by-side walking model for an interacting robot. J. Hum.-Robot Interact. 3(2), 50–73 (2014)CrossRefGoogle Scholar
  21. 21.
    Nakazawa, K., Takahashi, K., Kaneko, M.: Movement control of accompanying robot based on artificial potential field adapted to dynamic environments. Electr. Eng. Jpn. 192(1), 25–35 (2015)CrossRefGoogle Scholar
  22. 22.
    Narzt, W., Wilflingseder, U., Pomberger, G., Kolb, D., Hörtner, H.: Self-organising congestion evasion strategies using ant-based pheromones. IET Intel. Transp. Syst. 4(1), 93–102 (2010)CrossRefGoogle Scholar
  23. 23.
    Peternel, L., Tsagarakis, N., Caldwell, D., Ajoudani, A.: Robot adaptation to human physical fatigue in human-robot co-manipulation. Auton. Robots 42, 1–11 (2018)CrossRefGoogle Scholar
  24. 24.
    Petit, M., Lallée, S., Boucher, J.D., Pointeau, G., Cheminade, P., Ognibene, D., Chinellato, E., Pattacini, U., Gori, I., Martinez-Hernandez, U., et al.: The coordinating role of language in real-time multimodal learning of cooperative tasks. IEEE Trans. Auton. Ment. Dev. 5(1), 3–17 (2013)CrossRefGoogle Scholar
  25. 25.
    Roncone, A., Mangin, O., Scassellati, B.: Transparent role assignment and task allocation in human robot collaboration. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 1014–1021. IEEE (2017)Google Scholar
  26. 26.
    Susnea, I., Vasiliu, G., Filipescu, A., Radaschin, A.: Virtual pheromones for real-time control of autonomous mobile robots. Stud. Inform. Control 18(3), 233–240 (2009)Google Scholar
  27. 27.
    The, V.N., Jayawardena, C.: A decision making model for optimizing social relationship for side-by-side robotic wheelchairs in active mode. In: IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp. 735–740 (2016)Google Scholar
  28. 28.
    Tomasello, M., Carpenter, M.: Shared intentionality. Dev. Sci. 10(1), 121–125 (2007)CrossRefGoogle Scholar
  29. 29.
    Van Ginkel, W., Tindale, R.S., Van Knippenberg, D.: Team reflexivity, development of shared task representations, and the use of distributed information in group decision making. Group Dyn.: Theory Res. Pract. 13(4), 265 (2009)CrossRefGoogle Scholar
  30. 30.
    Vander Meer, R.K., Breed, M.D., Espelie, K.E., Winston, M.L.: Pheromone Communication in Social Insects. Ants, Wasps, Bees and Termites, vol. 162. Westview, Boulder (1998)Google Scholar
  31. 31.
    Wykowska, A., Chellali, R., Al-Amin, M.M., Müller, H.J.: Implications of robot actions for human perception. How do we represent actions of the observed robots? Int. J. Soc. Robot. 6(3), 357–366 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Marc Dalmasso
    • 1
    Email author
  • Anaís Garrell
    • 1
  • Pablo Jiménez
    • 1
  • Alberto Sanfeliu
    • 1
  1. 1.Institut de Robòtica i Informàtica Industrial (CSIC-UPC)BarcelonaSpain

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