A Human-Robot Competition: Towards Evaluating Robots’ Reasoning Abilities for HRI

  • Amit Kumar PandeyEmail author
  • Lavindra de Silva
  • Rachid Alami
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9979)


For effective Human-Robot Interaction (HRI), a robot should be human and human-environment aware. Perspective taking, effort analysis and affordance analysis are some of the core components in such human-centered reasoning. This paper is concerned with the need for benchmarking scenarios to assess the resultant intelligence, when such reasoning blocks function together. Despite the various competitions involving robots, there is a lack of approaches considering the human in their scenarios and in the reasoning processes, especially those targeting HRI. We present a game that is centered upon a human-robot competition, and motivate how our scenario, and the idea of a robot and a human competing, can serve as a benchmark test for both human-aware reasoning as well as inter-robot social intelligence. Based on subjective feedback from participants, we also provide some pointers and ingredients for evaluation matrices.


Ground Truth Perspective Taking Benchmark Test Taskability Graph Social Intelligence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Csibra, G., Volein, A.: Infants can infer the presence of hidden objects from referential gaze information. Br. J. Dev. Psychol. 26(1), 1–11 (2008)CrossRefGoogle Scholar
  2. 2.
    Rochat, P.: Perceived reachability for self and for others by 3 to 5-year old children and adults. J. Exp. Child Psychol. 59, 317–333 (1995)CrossRefGoogle Scholar
  3. 3.
    Breazeal, C., Berlin, M., Brooks, A.G., Gray, J., Thomaz, A.L.: Using perspective taking to learn from ambiguous demonstrations. Robot. Auton. Syst. 54, 385–393 (2006)CrossRefGoogle Scholar
  4. 4.
    Trafton, J.G., Schultz, A.C., Bugajska, M., Mintz, F.: Perspective-taking with robots: experiments and models. In: IEEE International Workshop on Robots and Human Interactive Communication (RO-MAN), pp. 580–584 (2005)Google Scholar
  5. 5.
    Marin-Urias, L., Sisbot, E., Pandey, A., Tadakuma, R., Alami, R.: Towards shared attention through geometric reasoning for human robot interaction. In: Proceedings of 9th IEEE-RAS International Conference on Humanoid Robots (Humanoids), pp. 331–336 (2009)Google Scholar
  6. 6.
    Gibson, J.J.: The theory of affordances. In: The Ecological Approach to Visual Perception, pp. 127–143. Psychology Press (1986)Google Scholar
  7. 7.
    Clark, A.: An embodied cognitive science? Trends. Cogn. Sci. 3(9), 345–351 (1999)CrossRefGoogle Scholar
  8. 8.
    Stoytchev, A.: Behavior-grounded representation of tool affordances. In: Proceedings of ICRA, pp. 3060–3065 (2005)Google Scholar
  9. 9.
    Ugur, E., Dogar, M.R., Cakmak, M., Sahin, E.: Curiosity-driven learning of traversability affordance on a mobile robot. In: IEEE International Conference on Development and Learning (ICDL), pp. 13–18, July 2007Google Scholar
  10. 10.
    Lopes, M., Melo, F.S., Montesano, L.: Affordance-based imitation learning in robots. In: Proceedings of IROS, pp. 1015–1021 (2007)Google Scholar
  11. 11.
  12. 12.
    DARPA robotics challenge (DRC).
  13. 13.
    European land-robot trial (elrob).
  14. 14.
    Humabot robot competition.
  15. 15.
  16. 16.
  17. 17.
    Pandey, A.K., de Silva, L., Alami, R.: A novel concept of human-robot competition for evaluating a robot’s reasoning capabilities in HRI. In: International Conference on Human-Robot Interaction (HRI), pp. 491–492 (2016)Google Scholar
  18. 18.
    Pandey, A.K., Alami, R.: Affordance graph: a framework to encodeperspective taking and effort based affordances for day-to-day human-robotinteraction. In: Proceedings of IROS, pp. 2180–2187 (2013)Google Scholar
  19. 19.
    Gardner, D.L., Mark, L.S., Ward, J.A., Edkins, H.: How do task characteristics affect the transitions between seated and standing reaches? Ecol. Psychol. 13(4), 245–274 (2001)CrossRefGoogle Scholar
  20. 20.
    Fleury, S., Herrb, M., Chatila, R.: Genom: a tool for the specification and the implementation of operating modules in a distributed robotarchitecture. In: Proceedings of IROS, pp. 842–848 (1997)Google Scholar
  21. 21.
    Simeon, T., Laumond, J.-P., Lamiraux, F.: Move3D: a generic platform for path planning. In: 4th International Symposium on Assembly and Task Planning, pp. 25–30 (2001)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Amit Kumar Pandey
    • 1
    Email author
  • Lavindra de Silva
    • 2
  • Rachid Alami
    • 3
  1. 1.SoftBank Robotics, Innovation DepartmentParisFrance
  2. 2.Institute for Advanced ManufacturingUniversity of NottinghamNottinghamUK
  3. 3.LAAS-CNRSUniversity of ToulouseToulouseFrance

Personalised recommendations