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that the technology of fully decentralized robotic systems is
mature enough to provide a robust basis for human factor
studies in the field-a first for robotics swarms. The small
sample of operators involved does not guarantee the generalization of the human findings, but it does suggest that
both objective and subjective measures will help us understand and improve HSIs. From the subjective measures, we
learned that managing up to five UAVs simultaneously is
still feasible for both the more autonomous and less autonomous control modes; greater benefits of autonomy are likely
to be realized as systems are scaled up. We also observed
that the uncertainty of the output from the swarm's selforganized behavior led to operator confusion, insecurity,
and greater perceived cognitive load. It appears that workload can partly be disentangled from perceived control
using objective physiological measures, such as pupillometry. The pupil dilation data seem to indicate that the mode
with greater autonomy (self-deployment) is indeed less
demanding. Nonetheless, the results point to a need for
interfaces that communicate prospective swarm behavior
more clearly if the full potential of autonomous swarms is to
be realized. Our results motivate work on more intuitive
command centers, such as new graphic overlays of prospective swarm behavior on the mission planner, or on a tangible
table interface that replaces the mission planner entirely. We
believe that swarm intelligence deployment in planetary
exploration missions has a promising future and that the
technology will also be applicable to many Earth-based
mobile autonomous systems.
We are currently conducting a larger experiment to allow
for statistical comparisons between conditions. While still
using swarms of real robots, a miniature indoor setup will
require less preparation time and ensure more stable environmental and luminance conditions, facilitating human
measurements. We will also complement pupillometry with
measures of skin conductivity and heart-rate variability,
which have different physiological bases and will provide a
more complete perspective on the operator's state. To firmly
anchor our contributions to the development of technologies
for space exploration, we are now adapting our tools for
ground-to-air robotic teams in lava tubes. These regions are
difficult to observe from space but may well be the most suitable environments for safe settlements on the moon and
Mars [44].
Acknowledgments
We would like to acknowledge the invitation of the Europrean Space Agency and the support of the PANGAEA-X logistics team. This research was partially funded by Natural
Sciences and Engineering Research Council grants, and half
of the fleet was designed and adapted to our needs by Pleiades Robotics.
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https://www.nasa.gov/centers/ames/research/technology-onepagers/mars-airplane.html https://www.nasa.gov/centers/ames/research/technology-onepagers/mars-airplane.html https://www.github.com/MISTLab/buzz https://www.github.com/MISTLab/buzz https://www.github.com/MISTLab/ROSBuzz http://www.arxiv.org/abs/1710.08843
IEEE Robotics & Automation Magazine - June 2020

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