Hello everyone, my name is Emmanuel Senft,
I am currently working at the University of Wisconsin-Madison.
But in this talk, I will present work that I have been doing with Satoru Satake
and Takayuki Kanda at ATR in Japan.
The title of the talk is: Would you mind me if I pass by you?
And with this work, we want to explore how a robot should behave
when crossing people in narrow corridors.
Picture this situation.
There is a robot in a shop, and this robot might belong to a client or to the shop owner.
And, to accomplish its task, the robot must navigate in the environment
and potentially cross with people.
This is the situation we are considering,
the robot must cross a corridor, and someone is coming toward it.
In this case, the optimal robot behavior is unknown, for example, the robot might go on
the side and follow the wall, letting the human pass
or maybe it would be better for the robot to just stop and wait.
This is what we are trying to figure out with this work.
Human-aware navigation is not a new topic in HRI, a lot of research has been done already.
The classic approach is to find a collision free trajectory, while still considering proxemics,
some social norms (such as not approaching people from behind)
and the probability of human motion.
However, narrow corridor navigation has two very specific characteristics.
First, there is very limited lateral space, and second, parties have clear goals and need
to cross each other in the environment.
For humans, this type of interaction is natural and easy.
However, as mentioned previously, for robots, it is unclear what the optimal behavior should be,
and failing to meet expectations could annoy or worry the human partner.
To find the factors that matter in such interaction, we started by observing how humans do it.
Then from these observations, we created a model of human behavior,
implemented it on a robot and then evaluated it in a human-robot study.
For our observational study, we asked members of the lab
to navigate in a space representing a convenient store in Japan.
And when they crossed each other, the typic behavior we observed was the following one.
First, the person started to step on the side, to free space in the corridor.
Then she moved forward, making a sliding motion.
And just in time before crossing, she rotated her upper body.
After the rotation, she kept moving forward and finally went back to the middle.
We modelled this behavior into three parts: first, the step, where the person goes on
the side to free space in the corridor, then the slide, when people are approaching each
other, and finally, the rotation, just in time before the crossing.
Two factors in this model are especially important: the body orientation and the forward motion.
The body orientation refers to a change of the upper body’s direction compared to the trajectory.
And the forward motion represents the fact that people often do not just stop
but keep moving forward while crossing.
It is important to note that the body rotation can be made in two directions.
The first one is the open rotation, it means that the person is rotating to face the other
one and it is used mostly by men.
The second one is the close rotation, which exposes the back of the body
and is mostly used by women.
In our implementation, we used an open rotation because it actually provides more space for
the incoming person, while a closed rotation could invade private space by moving the shoulder forward.
The first image shows the robot moving toward its goal, and when a human is on its way,
as in image 2, the robot plans an avoiding path, containing the step and the forward
motion and just in time before the crossing, the robot rotates its body to free space as
shown in image 4, before going back to the center of the corridor.
During our pilot studies we realized that three considerations are especially important
when implementing this type of behavior.
First, the initial step must be visible
to convey the robot’s intention to get out of the way.
Second, the sliding motion needs to be really smooth as small deviations could result in
invasion of private space which could be uncomfortable for the human.
And finally, the timing of the rotation is important too, as a rotation too early would
miss the context and one too late would lose its purpose.
To evaluate our implementation we designed a study where a robot was acting as a clerk
in a simulated shop and with this study, we explored how the rotation and the sliding
motion impacted people’s perception when crossing the robot.
This diagram represents the setup we used in our study, the participant and the robot are
in this simulated shop and the experimenter is on the side.
The participant must pick predefined items in the shop,
so that she crosses the robot on the long aisle.
This picking task is repeated three times per condition.
Our hypotheses are the following ones: a robot rotating its body would be following human
social norms and as such would be perceived as more natural and likeable.
We use the warmth measure from the RoSAS scale as a proxy for naturalness.
Similarly, a robot sliding forward instead of stopping would be perceived as warmer and more likeable.
Our design explored these two factors: rotation vs no-rotation and slide vs no-slide,
which resulted in four conditions and we adopted a within participants design.
We analyzed results from 23 participants, and each participant interacted with each
of the four conditions in a counter-balanced order.
This video from the study presents an example of the robot behavior when sliding and rotating.
First, the robot steps on the side, then it slides forward and just in time before crossing
the person, it rotates its body before going back to the middle of the corridor.
On the other hand, this video presents an example of the no-slide, no-rotation condition.
As before, the robot starts by stepping on the side,
but then, it stops and does not move forward.
And even when the person is approaching, the robot does not rotate.
Finally, when the person is behind the robot, it goes back to the middle of the corridor
and continues towards its goal.
In our implementation, the direction of the step was based on the human initial position
and the robot automatically decided to go on the left or right side.
During the study, we witnessed some interesting behaviors from our participants.
For example, this one nodded to the robot
maybe to show appreciation for considering him.
Look at the head of the participant, he moves forward, and just as the robot rotate its
body, the participant nodded, and this happened only when the robot rotated its body.
The first part of our results concerns the warmth evaluation from the RoSAS.
When evaluating the warmth, we observed that both factors:
the rotation and the motion had a significant impact.
However, the interaction was not significant.
The second part of our results concerns the likeability evaluation from the Godspeed Questionnaire.
For the likeability, we only measured a significant difference for the rotation,
both the motion and the interaction were not significant.
To understand our results, we analyzed semi-structured interviews
we had with the participants after each condition.
Participants reported that when the robot was rotating its body, they found it welcoming and caring,
even if some noted that they felt observed as the robot was continuously looking at them.
However, when the robot was moving forward and not rotating, participants described it
as rushing, it had a task and was just doing it, while still avoiding them.
Finally, when the robot was not sliding and not rotating, participants noted the lack
of agency: it was inorganic and could be an obstacle.
To conclude, our hypotheses are partially supported.
A robot rotating its body is indeed perceived as warmer and more likeable.
However, a robot sliding forward is only perceived as warmer, but not more likeable.
This disparity between warmth and likeability could be due to the fact that warmth does
include items related to agency which might not lead to a higher likeability.
Our paper’s take home message is the following one:
social navigation goes beyond simple collision free trajectory.
The community knows already that a large number of other modalities are important,
such as social norms, speech and gaze for example.
But with this work, we want to add to these previous findings,
and we showed that body orientation does matter,
and by taking this into account, we believe that as a community,
we could enrich social navigation.
Thank you very much for your attention.