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How a Minimally Designed Robot can Help Implicitly Maintain the Communication Protocol

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Abstract

With an increasing demand for minimally designed robots, the research field of human–robot interaction (HRI) has to meet new and challenging requirements. One of these challenges is in the difference between the user’s retained mental model consisting of the instructions triggering the robot’s different behaviors and the robot’s previously taught instructions by the user. More specifically, we mention here the divergence between what was remembered by the non-expert user or believed taught to the robot in a previous HRI instance and what was actually taught to it. This divergence could lead to a waste of time when the robot is reused before it could be used effectively to achieve a task. Some users may not have the patience to reteach the robot a new version of instructions or what we call a communication protocol (CP) if they realize that they have forgotten the previous version of CP. In our previous work, we studied how a non-expert user could establish a CP in a context that required mutual adaptation using a minimally designed robot named sociable dining table (SDT). SDT is a dish robot, placed on a table which behaves according to knocks issued by the human. The human knocks on the table to convey an instruction in order to make the SDT undertake a specific behavior. The SDT had to learn through the received knocking how to choose the correct behavior. We remarked, based on previous experiments, that a CP could be built incrementally during the HRI. The formed CP was not only personalized to the pair of the non-expert user and robot, but also to the HRI instance. This means that the CP changed each time the human started a new interaction session with the SDT. The main reason behind the change was the non-expert users’ forgetfulness of the previously established communication protocol (PECP) and their issuing of a different set of new instructions to the SDT rather than maintaining the old instructions and continuing to teach the robot new skills. In the current study, we investigate how we can modify the way the minimally designed robot communicates back to the human so that the CP could be maintained and time wasted constructing a new CP could be avoided. This paper describes feedback strategies combining inarticulate utterances (IUs) with the minimally designed robot’s visible behaviors, to trigger an increased remembrance of the PECP. The results provide confirmatory evidence that using IUs combined with the minimally designed robot’s visible behaviors assist in driving non-expert users to maintain the PECP and avoid time wastage and task achievement failure.

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Notes

  1. Reinforcement learning refers to a class of machine learning problems. The aim is to learn from experience, what to do in different situations, so as to optimize a quantitative reward over time.

  2. Here we mention about a reward signal that should be assigned in such a way so the robot could clearly distinguish between the right and wrong behaviors. A wrong behavior is associated with a negative reward signal, while a good behavior is associated with a positive reward signal.

  3. By expressive feedback strategy, we mean a feedback that makes it easy for the human to identify the wrong instructions given by him to the robot. In the current work, what we mean by new expressive feedback is a combination of the robot’s visible behaviors with the IUs.

  4. It is a cued recall because the robot tries to help the human to remember the rules by presenting cues which are in a sound format.

  5. E1 refers to the first ensemble (E) of IUs that could be generated to indicate that the robot is about to execute the forward behavior. The IUs used in the ensemble E1 do not figure in the E2 to avoid any kind of confusion. For example, the user may listen (if we suppose that A, B and C are IUs) to one of the three IUs A, B or C when the robot is about to execute the forward behavior, etc.

  6. Continuous-knocking was related to the presence of contiguous disagreements about the shared rules.

  7. https://goo.gl/forms/Vr6LVRDS99wBFMHX2.

  8. By “implicit” in this context we mean that the robot has not to tell directly to the human that they introduced a different instruction’s version than the actual previously taught instruction. The human can remember indirectly when the IU triggers their memory during the robot’s reuse, the previously taught instruction.

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Acknowledgements

This research is supported by Grant-in-Aid for scientific research of KIBAN-B (26280102) from the Japan Society for the Promotion of science (JSPS).

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  1. Interaction and Communication Design Lab, Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku, Toyohashi, Aichi, Japan

    Khaoula Youssef & Michio Okada

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  1. Khaoula Youssef
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Correspondence to Khaoula Youssef.

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Youssef, K., Okada, M. How a Minimally Designed Robot can Help Implicitly Maintain the Communication Protocol. Int J of Soc Robotics 9, 431–448 (2017). https://doi.org/10.1007/s12369-017-0398-7

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