309
A Test Environment for Studying Robotic Eye Movements
processing, signal transmission, and dead times, which amounted to 1.5,
1.2, and 1.8 ms, respectively (see Figure 16.6).
In addition to the eye-tracker delay of 10 ms, the delay of the analog video
transmission for the scene view (see Figure 16.1) needs to be considered. We
measured this delay by using a flashing LED in front of ELIAS’s scene camera and a photodiode on the wizard’s video monitor. This delay amounted
to 20 ms. The total delay in the virtual interaction loop was therefore 30 ms.
This is just a fraction of the typical human reaction time of 150 ms.
For the wireless link, we measured a latency between 50 and 80 ms depending on synchronization of the camera and monitor, which led to an overall
mean latency of 75 ms.
16.4 Conclusion and Future Work
In this work we proposed a novel paradigm for the evaluation of human–
robot interaction, with special focus on the importance of natural eye and
head movements in human–machine communication scenarios. We also
presented a unique experimental platform that will enable Wizard-of-Oz
experiments in which a human experimenter (wizard) teleoperates a
robotic head and eyes with his own head and eyes. The platform mainly
consists of an eye and head tracker and motion devices for the robot head
and his eyes, as well as a feedback video transmission link for the view
of the experimental scene. We demonstrated that the eye tracker can
measure the whole dynamical range of eye movements and that these
movements can be replicated by the novel robotic eyes with more than
sufficient fidelity. The camera motion device developed combines small
dimensions with dynamical properties that exceed the requirements
posed by the human ocular motor system. In addition, by reducing all
critical delays to a minimum, we met the rigid real-time requirements
of an experimental platform that is designed to enable seamless human–
machine interactions.
Preliminary evaluation with human subjects showed a high acceptance of
the system. In future experiments we intend to answer the question of how
important it is to resemble human performance in artificial eyes and which
aspects of ocular and neck motor functionality are key to people’s attribution
of humanness to robotic active vision systems. Possible experiments might
examine the effects on human–robot interaction performance while the teleoperation channel is manipulated, for example, with artificial delays.
We also plan to control even more aspects of the robot by the wizard, for
example, the eyelids (which directly map to the wizard’s eye lids) or mouth
movements, which would require an additional camera that tracks the wizard’s mouth area.
A Test Environment for Studying Robotic Eye Movements
processing, signal transmission, and dead times, which amounted to 1.5,
1.2, and 1.8 ms, respectively (see Figure 16.6).
In addition to the eye-tracker delay of 10 ms, the delay of the analog video
transmission for the scene view (see Figure 16.1) needs to be considered. We
measured this delay by using a flashing LED in front of ELIAS’s scene camera and a photodiode on the wizard’s video monitor. This delay amounted
to 20 ms. The total delay in the virtual interaction loop was therefore 30 ms.
This is just a fraction of the typical human reaction time of 150 ms.
For the wireless link, we measured a latency between 50 and 80 ms depending on synchronization of the camera and monitor, which led to an overall
mean latency of 75 ms.
16.4 Conclusion and Future Work
In this work we proposed a novel paradigm for the evaluation of human–
robot interaction, with special focus on the importance of natural eye and
head movements in human–machine communication scenarios. We also
presented a unique experimental platform that will enable Wizard-of-Oz
experiments in which a human experimenter (wizard) teleoperates a
robotic head and eyes with his own head and eyes. The platform mainly
consists of an eye and head tracker and motion devices for the robot head
and his eyes, as well as a feedback video transmission link for the view
of the experimental scene. We demonstrated that the eye tracker can
measure the whole dynamical range of eye movements and that these
movements can be replicated by the novel robotic eyes with more than
sufficient fidelity. The camera motion device developed combines small
dimensions with dynamical properties that exceed the requirements
posed by the human ocular motor system. In addition, by reducing all
critical delays to a minimum, we met the rigid real-time requirements
of an experimental platform that is designed to enable seamless human–
machine interactions.
Preliminary evaluation with human subjects showed a high acceptance of
the system. In future experiments we intend to answer the question of how
important it is to resemble human performance in artificial eyes and which
aspects of ocular and neck motor functionality are key to people’s attribution
of humanness to robotic active vision systems. Possible experiments might
examine the effects on human–robot interaction performance while the teleoperation channel is manipulated, for example, with artificial delays.
We also plan to control even more aspects of the robot by the wizard, for
example, the eyelids (which directly map to the wizard’s eye lids) or mouth
movements, which would require an additional camera that tracks the wizard’s mouth area.