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120 MOTION PLANNING FOR A MOBILE ROBOT
T
S
Figure 3.20 Example of a walk (dashed line) in a maze under Algorithm VisBug-21
(compare with Figure 3.11). S,Start; T ,Target.
in a crowded scene where at any given moment it can see only a small part of the
scene, the efficacy of vision will be obviously limited. Nevertheless, unless the
scene is artificially made impossible for vision, one can expect gains from it. This
can be seen in performance of VisBug-21 algorithm in the maze borrowed from
Section 3.3.2 (see Figure 3.20). For simplicity, assume that the robot’s radius of
vision goes to infinity. While this ability would be mostly defeated here, the path
still looks significantly better than it does under the “tactile” algorithm Bug2
(compare with Figure 3.11).
3.6.3 Algorithm VisBug-22
The structure of this algorithm is somewhat similar to VisBug-21. The difference
is that here the robot makes no attempt to ensure that intermediate targets T i lie
on the Bug2 path. Instead, it tries “to shoot as far as possible”; that is, it chooses
as intermediate targets those points that lie on the M-line and are as close to
the target T as possible. The resulting behavior is different from the algorithm
VisBug-21, and so is the mechanism of convergence.