Page 53 - Introduction to AI Robotics

36
1 From Teleoperation To Autonomy
the camera. Is the dark region a canyon? Is it a shadow? The rover will
need to use inference to either actively or passively disambiguate what
the dark region is (e.g., kick a rock at the dark area versus reason that
there is nothing nearby that could create that shadow).

SEARCH 6. Search. Search doesn’t necessarily mean searching a large physical space
for an object. In AI terms, search means efficiently examining a know-
ledge representation of a problem (called a “search space”) to find the
answer. Deep Blue, the computer that beat the World Chess master Gary
Kasparov, won by searching through almost all possible combinations of
moves to find the best move to make. The legal moves in chess given the
current state of the board formed the search space.

VISION 7. Vision. Vision is possibly the most valuable sense humans have. Studies
by Harvard psychologist Steven Kosslyn suggest that much of problem
solving abilities stem from the ability to visually simulate the effects of
actions in our head. As such, AI researchers have pursued creating vision
systems both to improve robotic actions and to supplement other work in
general machine intelligence.

Finally, there is a temptation to assume that the history of AI Robotics is the
story of how advances in AI have improved robotics. But that is not the
case. In many regards, robotics has played a pivotal role in advancing AI.
Breakthroughs in methods for planning (operations research types of prob-
lems) came after the paradigm shift to reactivity in robotics in the late 1980’s
showed how unpredictable changes in the environment could actually be ex-
ploited to simplify programming. Many of the search engines on the world
wide web use techniques developed for robotics. These programs are called
SOFTWARE AGENTS software agents: autonomous programs which can interact with and adapt to
WEB-BOT their world just like an animal or a smart robot. The term web-bot directly
reflects on the robotic heritage of these AI systems. Even animation is being
changed by advances in AI robotics. According to a keynote address given
by Danny Hillis at the 1997 Autonomous Agents conference, animators for
Disney’s Hunchback of Notre Dame programmed each cartoon character in the
crowd scenes as if it were a simulation of a robot, and used methods that will
be discussed in Ch. 4.