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The Machbanai robot still has some room for improvement. The robot,
for example, gets caught on particularly tall pieces in other squares on
some occasions. The robot could use an extra touch sensor on the track to
detect when the robot is caught on a piece. The choice is to either
pause and let a human intervene or take a guess as to the direction in
which the robot should move.
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To conclude, let's review the project's goals and evaluate whether
we've been successful.
- Learn a new flavour of C (NQC).
Success.
- Program a robot to accept chess moves.
Success.
- Learn to integrate multiple projects (vision, robotics, and
A.I.)
Great success!!! Our robot gets out of the way for the vision
group to do their thing, it accepts commands from a LISP A.I. program, and
performs piece placement with near-perfect accuracy!
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