Hello, in this video we will present our paper:
Exploring Machine-like Behaviors for Socially Acceptable Robot Navigation in Elevators
My name is Danilo, and along Shreepriya,
we will be presenting this work on behalf of our colleagues Antonietta, Cecile, and Tommaso .
We started our work with the objective of defining socially acceptable behaviors
for autonomous robots that are meant to share an elevator with humans.
This scenario is relevant for our company, as we are working on the new HQ building in which
a fleet of robots like the one visible in the image will be introduced for delivery activities.
However, it is also relevant for the introduction of robots
in any building meant to be shared with humans.
The first question that arose was, what are socially acceptable behaviors
for robots in a scenario like this.
Indeed, it is a particularly interesting questions in this context,
as this scenario includes the sharing of limited spaces with humans,
subtle negotiations of space and priority that require high level of social competence,
and a scenario in which we can find a range of different states that the robot needs to communicate.
Finally, we have seen limited work exploring social acceptability in this context.
We began our research by conducting ethnographic observations
to try to understand how people use the elevators. We looked at the general patterns including the
use of space and artifacts, as well as the non-verbal communication practices.
Ethnographers in our team analysed 16 hours of video data recorded in
the elevator lobby of our company’s building in Korea, and indexed a total of 543 events.
Their focus was mostly on two points. The strategies used to establish the order of service,
for example, in the first image we see how two people gave priority to a third person
using a vow. And how people wait alone or in groups, for example, on the second image we
see a group of people waiting for another member before entering in the elevator.
From the ethnographic study we understood that people do not form structured queues,
but rather follow a weak first-come-first-serve principle. In a setting with multiple elevators,
priority is established through position and posture, and may be subject to renegotiation
through the use of non-verbal cues. Based on this, we concluded that even if we
had the required situation modelling technology, the nuances of the context would still be hard to
capture. In fact, the intention of people was not always clear even for human observers .
This motivated us to explore machine-like behaviors that can overcome some of the
limitations of fully imitating human behaviors. Machine-like behaviors should not require complex
inferences about the sensed social behaviors, but still avoid disrupting existing routines,
unlike exiting robots that for example use loud voice messages to express their intention.
Finally, we believe that this approach can limit the illusion of social competence,
as the robot behavior would not generate false expectation about its social capabilities.
We conducted a bodystorming session in order to explore our approach and define how
machine-like behaviors would look like in this context.
The session lasted 1 hour and included 4 researchers involved in the project .
Inspired by the situations observed during the ethnographic study, we simulated the elevator use
and one person at a time took the role of the robot, first enacting a human-like behavior, then
discussing what was not feasible with our robotic platform or was not considered comfortable.
For example, participants preferred to have the robot on a visible
position, rather than queuing behind them.
Finally, we bodystormed alternative behaviors,
which we considered as input to define a machine-like approach.
This activity provided us with guidelines for human behaviour
and machine-like behaviour elements that the robot should have.
Next, we conducted an online study to evaluate our approach
of adopting machine-like behaviours within our context. We had the following hypotheses:
1. People will prefer a clear differentiation of the robot behaviours from the queuing behaviour
by humans when waiting for the elevator. 2. People will prefer humans to have
priority over robots rather than respecting the order of arrival.
3. People will have different position preferences for robots and humans inside the elevator.
We conducted an online survey study with 223 recruited participants from Korea, US, and France.
Our survey included 22 multiple choice questions followed by mandatory open-ended
comments that helped us understand the underlying reasons for their preference.
All the collected quantitative results were analysed to validate our hypotheses
and also tested for correlation with participants’ characteristics.
We collected over 3600 written comments which were analysed using thematic analysis.
For queuing, as shown in the figure, we presented two animations.
The first one showed the robot taking place among people in an unstructured queue to wait for the
elevator, and the second one showed the robot taking a fixed position next to the elevator door.
60% of our participants preferred that a robot takes a fixed position rather than queuing and
waiting in a constantly evolving human line. We can validate our first hypothesis based on a test
of proportions. Our participants expressed that it was “natural” for the robot to behave differently.
We also only found a correlation between previous experience and choice of queuing.
People with experience preferred the first option
compared to people without experience. We can speculate that participants with prior
experience are more aware of the potential disruptiveness of the robot’s movements.
To understand what people perceive as the correct order of service in this context,
we asked questions regarding the participant’s willingness to let
the robot enter or exit first in different orders of arrival.
We found that most people would generally respect the order of arrival
to define the priority to enter the elevator.
This does not support our second hypothesis, but, interestingly, 40% would still claim priority
over the robot, even when the robot arrives first. When defining priority to exit a shared elevator,
51% would expect the robot to exit last, after humans.
There are two main reasons for our participants to give priority to humans. One is the ontological
difference between humans and robots, and the second is related to the efficiency of elevator
use. There is an assumption that the robot will be slow, and it will be more efficient
to let the humans move first, giving the robot more space and time to perform the movements.
We also wanted to understand the most preferred positions for the
robot inside an elevator and how and why these preferences change between a robot and a human.
As seen in the figures, we provided a top view of the elevator divided in a grid
identified by letters. Here, participants selected the preferred position for the human or the robot.
The corner positions opposite the button panels, i.e., G and A, were most preferred
for robots in small elevators, and Position M was most preferred in the large elevator.
For themselves, corner positions at the back of the elevator were most preferred.
These positions were different from robots, as also calculated through the Manhattan distance.
This supports our third hypothesis. The reason for different placements was to be not disruptive to
humans for entering, exiting or using the button panel. Please refer to our paper for more details.
We found that a pure human-like behaviour policy for a robot
is not feasible, as described in our ethnographic observations,
and not even desirable, as highlighted by the bodystorming and the survey results,
especially in this context where the aim is to create a non-experience for routine activity.
We also do not characterise machine-like and human-like as two extreme positions of
a spectrum. We rather advocate finding the right balance when designing policies that leverage:
(1) human-like behaviours to have a familiar and efficient interaction with the robots and ensure
that the robots blend into the social context, and (2) machine-like behaviours that better correspond
to human preferences and transparently communicate the limits of the robots’ ability
to handle only certain social interactions, based on the technical limitations.
We acknowledge that machine-like behaviours are unfamiliar, and to successfully introduce them,
communication modalities are crucial to convey the intent clearly. Hence, in the future,
we want to test different communication modalities that effectively convey the robot’s intent and
complement our machine-like approach. Furthermore, we plan to integrate the navigation policies
and effective communication modalities into a comprehensive service that can be deployed
in elevators and tested through in-situ experiments and naturalistic observations.
Thank you all for your attention.