Effects of the Interaction with Robot Swarms on the Human Psychological State

Human-swarm interaction studies how human beings can interact with a robotswarm---a large number of robots cooperating with each other without any form of centralizedcontrol. In today's human-swarm interaction literature, the large majority of the works investigatehow human beings can issue commands to and receive feedback from a robot swarm. However, only a few ofthese works study the effect of the interaction with a robot swarm on human psychology (e.g. on thehuman stress or on the human workload). Understanding human psychology in human-swarm interaction isimportant because the human psychological state can have significant impact on the way humansinteract with robot swarms (e.g. a high level of stress can cause a human operator to freeze in themiddle of a critical task, such as a search-and-rescue task). Most existing works that study human psychology in human-swarm interaction conduct their experimentsusing robot swarms simulated on a computer screen. The use of simulation is convenient becauseexperimental conditions can be repeated perfectly in different experimental runs and becauseexperimentation using real robots is expensive both in money and time. However, simulation suffersfrom the so-called reality gap: the inherent discrepancy between simulation and reality. Itis therefore important to study whether this inherent discrepancy can affect humanpsychology---human operators interacting with a simulated robot swarm can react differently thanwhen interacting with a real robot swarm.A large literature in human-robot interaction has studied the psychological impact of theinteraction between human beings and single robots. This literature could in principle be highlyrelevant to human-swarm interaction. However, an inherent difference between human-robot interactionand human-swarm interaction is that in the latter, human operators interact with a large number ofrobots. This large number of robots can affect human psychology---human operators interacting with alarge number of robots can react differently than when interacting with a single robot or with asmall number of robots. It is therefore important to understand whether the large number of robotsthat composes a robot swarm affects human psychology. In fact, if this is the case, it would not bepossible to directly apply the results of human-robot interaction research to human-swarminteraction.We conducted several experiments in order to understand the effect of the reality gap and the effectof the group size (i.e. the number of robots that composes a robot swarm) on the humanpsychological state. In these experiments our participants are exposed to swarms of robots and arepurely passive---they do not issue commands nor receive feedback from the robots. Making theinteraction passive allowed us to study the effects of the reality gap and of the group size on thehuman psychological state without the risk that an interaction interface (such as a joystick)influences the psychological responses of the participants (and thus limiting the visibility of both thereality gap and group size effects). In the reality gap experiments, participants are exposed tosimulated robot swarms displayed either on a computer screen or in a virtual reality environment, and toreal robot swarms. In the group size experiments, participants are exposed to an increasing numberof real robots.In this thesis, we show that the reality gap and the group size affect the human psychological stateby collecting psychophysiological measures (heart rate and skin conductance), self-reported (viaquestionnaires) affective state measures (arousal and valence), self-reported workload (the amountof mental resource needed to carry out a task) and reaction time (the time needed to respond to astimulus). Firstly, we show with our results that our participants' psychophysiological measures,affective state measures, workload and reaction time are significantly higher when they interactwith a real robot swarm compared to when they interact with a robot swarm simulated on a computerscreen, confirming that the reality gap significantly affects the human psychological state.Moreover, we show that it is possible to mitigate the effect of the reality gap using virtualreality---our participants' arousal, workload and reaction time are significantly higher when theyinteract with a simulated robot swarm displayed in a virtual reality environment as opposed to whenit is displayed on a computer screen. Secondly, we show that our participants' psychophysiologicalmeasures and affective state measures increase when the number of robots they are exposed toincreases. Our results have important implications for research in human-swarm interaction. Firstly, for thefirst time, we show that experiments in simulation change the human psychological state compared toexperiments with real robots. Secondly, we show that a characteristic that is inherent to thedefinition of swarm robotics---the large number of robots that composes a robotswarm---significantly affects the human psychological state. Finally, our results show thatpsychophysiological measures, such as heart rate and skin conductance, provide researchers with moreinformation on human psychology than the information provided by using traditional self-reportedmeasures (collected via psychological questionnaires).Doctorat en Sciences de l'ingénieur et technologieinfo:eu-repo/semantics/nonPublishe

Self-organised Feedback in Human Swarm Interaction

http://workshops.icts.sbg.ac.at/ro-man2012/?site=papersinfo:eu-repo/semantics/publishe

Gesturing at subswarms: Towards direct human control of robot swarms

The term human-swarm interaction (HSI) refers to the interaction between a human operator and a swarm of robots. In this paper, we investigate HSI in the context of a resource allocation and guidance scenario. We present a framework that enables direct communication between human beings and real robot swarms, without relying on a secondary display. We provide the user with a gesture-based interface that allows him to issue commands to the robots. In addition, we develop algorithms that allow robots receiving the commands to display appropriate feedback to the user. We evaluate our framework both in simulation and with real-world experiments. We conduct a summative usability study based on experiments in which participants must guide multiple subswarms to different task locations. © 2014 Springer-Verlag.SCOPUS: cp.kinfo:eu-repo/semantics/publishe

Human Responses to Stimuli Produced by Robot Swarms-the Effect of the Reality-Gap on Psychological State

info:eu-repo/semantics/publishe

Investigating the effect of increasing robot group sizes on the human psychophysiological state in the context of human–swarm interaction

We study the psychophysiological state of humans when exposed to robot groups of varying sizes. In our experiments, 24 participants are exposed sequentially to groups of robots made up of 1, 3 and 24 robots. We measure both objective physiological metrics (skin conductance level and heart rate), and subjective self-reported metrics (from a psychological questionnaire). These measures allow us to analyse the psychophysiological state (stress, anxiety, happiness) of our participants. Our results show that the number of robots to which a human is exposed has a significant impact on the psychophysiological state of the human and that higher numbers of robots provoke a stronger response.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

An experiment in automatic design of robot swarms AutoMoDe-vanilla, EvoStick, and human experts

We present an experiment in automatic design of robot swarms. For the first time in the swarm robotics literature, we perform an objective comparison of multiple design methods: we compare swarms designed by two automatic methods—AutoMoDe-Vanilla and EvoStick— with swarms manually designed by human experts. AutoMoDe-Vanilla and EvoStick have been previously published and tested on two tasks. To evaluate their generality, in this paper we test them without any modifi- cation on five new tasks. Besides confirming that AutoMoDe-Vanilla is effective, our results provide new insight into the design of robot swarms. In particular, our results indicate that, at least under the adopted experimental protocol, not only does automatic design suffer from the reality gap, but also manual design. The results also show that both manual and automatic methods benefit from bias injection. In this work, bias injection consists in restricting the design search space to the combinations of pre-existing modules. The results indicate that bias injection helps to overcome the reality gap, yielding better performing robot swarms.SCOPUS: ar.kinfo:eu-repo/semantics/publishe

AutoMoDe-Chocolate: automatic design of control software for robot swarms

We present two empirical studies on the design of control software for robot swarms. In Study A, Vanilla and EvoStick, two previously published automatic design methods, are compared with human designers. The comparison is performed on five swarm robotics tasks that are different from those on which Vanilla and EvoStick have been previously tested. The results show that, under the experimental conditions considered, Vanilla performs better than EvoStick, but it is not able to outperform human designers. The results indicate that Vanilla ’s weak element is the optimization algorithm employed to search the space of candidate designs. To improve over Vanilla and with the final goal of obtaining an automatic design method that performs better than human designers, we introduce Chocolate, which differs from Vanilla only in the fact that it adopts a more powerful optimization algorithm. In Study B, we perform an assessment of Chocolate. The results show that, under the experimental conditions considered, Chocolate outperforms both Vanilla and the human designers. Chocolate is the first automatic design method for robot swarms that, at least under specific experimental conditions, is shown to outperform a human designer.SCOPUS: ar.jinfo:eu-repo/semantics/publishe