Page 98 - Designing Sociable Robots

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The Vision System 79

6.5 Summary

There are many interesting ways in which Kismet’s attention system can be improved
and extended. This should not overshadow the fact that the existing attention system is an
important contribution to autonomous robotics research.
Other researchers have developed bottom-up attention systems (Itti et al., 1998; Wolfe,
1994). Many of these systems work in isolation and are not embedded in a behaving robot.
Kismet’s attention system goes beyond raw perceptual saliency to incorporate top-down
task-driven influences that vary dynamically over time with its goals. By doing so, the
attention system is tuned to benefit the task the robot is currently engaged in.
There are far too many things that the robot could be responding to at any time. The
attention system gives the robot a locus of interest that it can organize its behavior around.
This contributes to perceptual stability, since the robot is not inclined to flit its eyes around
randomly from place to place, changing its perceptual input at a pace too rapid for behavior
to keep up. This in turn contributes to behavioral stability since the robot has a target that
it can direct its behavior toward and respond to. Each target (people, toys) has a physical
persistence that is well-matched to the robot’s behavioral time scale. Of course, the robot
can respond to different targets sequentially in time, but this occurs at a slow enough time
scale that the behaviors have time to self-organize and stabilize into a coherent goal-directed
pattern before a switch to a new behavior is made.
There is no prior art in incorporating a task-dependent attentional system into a robot.
Some sidestep the issue by incorporating an implicit attention mechanism into the perceptual
conditions that release behaviors (Blumberg, 1994; Velasquez, 1998). Others do so by
building systems that are hardwired to perceive one type of stimulus tailored to the specific
task (Schaal, 1997; Mataric et al., 1998), or use very simple sensors (Hayes & Demiris, 1994;
Billard & Dautenhahn, 1997). However, the complexity of Kismet’s visual environment,
the richness of its perceptual capabilities, and its time-varying goals required an explicit
implementation.
The social dimension of Kismet’s world adds additional constraints that prior robotic
systems have not had to deal with. As argued earlier, the robot’s attention system must be
tuned to the attention system of humans. In this way, both robot and humans are more likely
to find the same sorts of things interesting or attention-grabbing. As a result, people can
very naturally and quickly direct the robot’s attention. The attention system coupled with
gaze direction provides people with a powerful and intuitive social cue. The readability and
interpretation of the robot’s behavior is greatly enhanced since the person has an accurate
measure of what the robot is responding to.
The ability for humans to easily influence the robot’s attention and to read its cues
has a tremendous benefit to various forms of social learning and is an important form of