IEEE Robotics & Automation Magazine - June 2019 - 44

Figure 4. The GUI to execute Romo actions.

Figure 5. The emotion game interface.

Table 1. Participant demographic information.
ID

Gender

Age (years)

Race

Group

1

M

10

Asian

TD

2

F

4

Asian

TD

3

M

9

Caucasian

TD

4

F

10

Caucasian

TD

5

M

9

Caucasian

TD

6

M

5

Caucasian

TD

7

M

5

Caucasian

TD

8

F

5

Caucasian

TD

9

M

5

Caucasian

TD

10

M

5

Caucasian

TD

11

M

9

South Asian

TD

12

M

7

Caucasian

ASD (HF)

13

M

8

Caucasian

ASD (HF)

14

M

10

Caucasian

ASD (HF)

15

M

8

Caucasian

ASD (HF)

16

M

9

Caucasian

ASD (LF)

17

M

8

South Asian

ASD (LF)

M: male; F: female; HF: high functioning; LF: low functioning.

44

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IEEE ROBOTICS & AUTOMATION MAGAZINE

*

JUNE 2019

the predetermined goal to facilitate ER. In this way, based on
continued interaction with the penguin character, the consensus algorithm attempts to guide the user toward the desired
target state.
This model determines the penguin character's next
emotion, as computed by (1) and (2). In the exchange of
emotions between the two agents, the initial emotional reactions of the penguin closely follow the user's emotion state
such that the penguin dynamically expresses emotions that
are similar to the user's emotion states. The penguin character's subsequent emotion selections then lead the user
toward the desired (goal) emotional state. Therefore, by
interacting with the user through a meaningful and sequential exchange of emotion, this algorithm enables the robot to
show distinct levels of empathy toward the user.
To test the feasibility of this approach, we designed a
turn-taking emotional-interaction game that uses the animated penguin character and its multiple emotional
expressions. The GUI designed for the application is shown
in Figure 5. The character initiates an interaction by displaying its current emotion state (left-side panel). The user
then responds by selecting his or her current emotion state
from the input panel in the middle, which is subsequently
displayed on the right-side panel. A temporary goal state is
computed and allocated, and the consensus algorithm is
run. This generates the character's next emotional response,
which is then displayed in the left-side panel. The character
continues to respond indefinitely until the user chooses to
quit the interaction.
User Study
Participants
We invited a total of 17 children between four and 12 years
of age to participate in our user study. The test group comprised six children with ASD, and the control group consisted of 11 typically developing (TD) children. The average age
of the test group was 8.33 years (with a standard deviation of
1.033 years), with six male participants. The average age of
the control group was 6.91 years (with a standard deviation
of 2.427 years), with eight male and three female participants. These are shown in Table 1, with the test group highlighted in blue.
Given the nature of the emotion game design, participants with some reading skills were better suited for this



IEEE Robotics & Automation Magazine - June 2019

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