Page 47 - Sensing, Intelligence, Motion : How Robots and Humans Move in an Unstructured World

22 MOTION PLANNING—INTRODUCTION

In manual guidance systems, a specially trained technician grabs the end tool
of the robot and performs the actual operation by moving it along the required
motion. The system automatically records all robot configurations along the path,
which can then be reproduced faithfully. The arm may be specially mechanically
balanced for easier motion, or be even completely replaced by a mockup arm that
includes all electronic means to document the motion in system’s memory. This
is similar to the situation when the choreographer physically moves a dancer’s
arm through the air, “That’s how you do it.” For example, in preparation for a
robot painting of a car body, an experienced human painter moves the arm with
the attached painting gun through the necessary motion, actually painting a car
body; the recorded motion is then used to paint a batch of car bodies.
While looking attractively simple, manual guidance systems are hard to real-
ize. For example, during actual job execution the robot must produce a perfectly
painted surface after a single motion, whereas a human painter can usually
use his powerful visual feedback to detect mistakes along the way and then
touch the paint here and there if needed. Various techniques have been designed
to mathematically “massage” the technician-taught motion to perfection—for
example, to assure the path curve smoothness or the robot end effector uni-
form speed.
The point-to-point teaching is a variation of the previous technique that dis-
poses with the real-time teaching. Here the human “teacher” brings the robot
end tool into the right position, pushes a button to save the corresponding robot
configuration in the robot memory, and goes to the next point, and so on, until
a set of points representing the whole path is accumulated. The set must then
be “massaged” in the above fashion, which is more difficult than in a manual
guidance system because the teaching session was removed from the real-time
operation and hence likely misses some important dynamic characteristics.
The teach pendant is a hardware accessory for point-to-point teaching. The
pendant is a small box connected with the robot by a cable, with a variety of
buttons for the operator to generate robot configurations. By intermittently giv-
ing increments in robot joint values—or alternatively, in Cartesian positions and
orientations of the robot tool—the operator brings the end effector to the desired
position, pushes a button to save it, and goes to the next position. This is a
tedious process: A reasonably complex path—say, painting a car engine com-
partment—may require 150–200 or more points, each requiring 40–60 button
pushes to produce it. The resulting path will likely need a considerable prepro-
cessing by a special software before being ready for actual use. Most of today’s
industrial robot programming systems are of this kind.
The off-line programming method is a logical and rather dramatic departure
from the techniques above, in that it tries to address their shortcomings by del-
egating the whole robot programming work to software. After all, each robot
configuration along the path is a function of the required path, which is in turn
a function of the task to which the motion applies. This motion can in principle
be coded in some specialized programming language, the way we write com-
puter programs. Hundreds of robot programming languages have been developed