Page 47 - Introduction to AI Robotics

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1 From Teleoperation To Autonomy

Figure 1.7 Sojourner Mars rover. (Photograph courtesy of the National Aeronautics
and Space Administration.)

Another example is the Sojourner robot (shown in Fig. 1.7) which explored
Mars from July 5 to September 27, 1997, until it ceased to reply to radio com-
mands. Since there was little data before Sojourner on what Mars is like,
it is hard to develop sensors and algorithms which can detect important at-
tributes or even control algorithms to move the robot. It is important that any
unusual rocks or rock formations (like the orange rock Dr. Schmitt found on
the Moon during Apollo 17) be detected. Humans are particularly adept at
perception, especially seeing patterns and anomalies in pictures. Current AI
perceptual abilities fall far short of human abilities. Humans are also adept
at problem solving. When the Mars Pathfinder craft landed on Mars, the
air bags that had cushioned the landing did not deflate properly. When the
petals of the lander opened, an airbag was in the way of Sojourner. The
solution? The ground controllers sent commands to retract the petals and
open them again. That type of problem solving is extremely difficult for the
current capabilities of AI.
But teleoperation is not an ideal solution for all situations. Many tasks
are repetitive and boring. For example, consider using a joystick to drive
a radio-controlled car; after a few hours, it tends to get harder and harder
to pay attention. Now imagine trying to control the car while only looking
through a small camera mounted in front. The task becomes much harder