Emotion Attribution to a Non-Humanoid Robot in Different Social Situations

Abstract

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human–animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour (“happiness” and “fear”), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot's greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot.

Humans attribute emotions to a robot that shows simple behavioural patterns borrowed from dog behaviour

“…The dog has already been successfully applied as the prototype of non-human companions in humanrobot interaction research (Ichikawa et al, 2012;Koay et al, 2013;Kovács, Vincze, Gácsi, Miklósi, & Korondi, 2009;Lakatos, Gácsi, et al, 2014;Syrdal, Koay, Gácsi, Walters, & Dautenhahn, 2010). Social robots are designed to actively interact with humans and, similarly to dogs, they need to fulfil double criteria: i) successful performance of the actions necessary for their specific function (i.e.…”

Implicit mind perception alters vigilance performance due to cognitive conflict processing

“…In order to test more directly if the stimuli used in the current experiment induced a cognitive conflict with regard to mind perception, we asked 55 participants (24 male; mean age= 36.8 years) in a post-hoc experiment to rate the stimuli regarding their ability of having a mind (i.e., using a Likert scale, following the procedure of Martini et al, 2016) and 161 participants (78 male; mean age= 33.8 years) in another post-hoc experiment to categorize the stimuli in a force-choice scenario into human and nonhuman (i.e., measuring percent of human versus non-human categorizations and reaction times, following the procedure of Lakatos, Gácsi, Konok, Brúder, Bereczky, Korondi, & Miklósi, 2014). Both experiments revealed that the humanoid stimulus was more difficult to classify than the other stimuli, as indicated by more ambiguous mind ratings, as well as less consensus and longer reaction times for the categorization of the humanoid stimulus compared to the other three stimuli; see Supplementary Materials (Section 1) for more details on the methods used and Figure 5 for a summary of the results.…”

Adaptive Fuzzy and Predictive Controllers for Expressive Robot Arm Movement during Human and Environment Interaction

“…The robot identification is implemented to determine the dynamic model related to the inertia matrix, Coriolis, gravitational and friction torque effects are shown in (1). The robust predictive controllers are designed according to the robot dynamic model, characterized by each joint motion.…”

“…The adaptive controllers allowed to generate robot motions with personalized interaction between human, environmental, and robot states. Experimental video of this work showing the expressive robot motion during the human and environmental interaction can be visualized in the link (1) .…”