Page 158 - Sensing, Intelligence, Motion : How Robots and Humans Move in an Unstructured World

DISCUSSION 133

Imagine we designed such a system: It is agile and compact; it is capable of
docking, repair, and hauling of space objects; and, to allow maneuvering around
space objects, it is equipped with a provable sensor-based motion planning algo-
rithm. Our robot—call it R-SAT—arrives to some old satellite “in a coma”—call
it X. The satellite X is not only moving along its orbit around the Earth, it is
also tumbling in space in some arbitrary ways. Before R-SAT starts on its repair
job, it will have to fly around X, to review its condition and its useability. It may
need to attach itself to the satellite for a more involved analysis. To do this—fly
around or attach to the satellite surface—the robot needs to be capable of speeds
that would allow these operations.
If the robot arrives at the site without any prior analysis of the satellite X
condition, this amounts to our choosing the first option above: No convergence
of R-SAT motion planning around X is guaranteed. On the other hand, a decision
to send R-SAT to satellite X might have been made after some serious remote
analysis of the X’s rate of tumbling. The analysis might have concluded that the
rate of tumbling of satellite X was well within the abilities of the R-SAT robot. In
our terms, this corresponds to adhering to the second option and to satisfying the
right constraints—and then the R-SAT’s motion planning will have a guaranteed
convergence.
Multirobot Groups. One area where the said constraints on obstacles’ motion
come naturally is multirobot systems. Imagine a group of mobile robots operating
in a planar scene. In line with our usual assumption of a high level of uncer-
tainty, assume that the robots are of different shapes and the system is highly
decentralized. That is, each robot makes its own motion planning decisions with-
out informing other robots, and so each robot knows nothing about the motion
planning intentions of other robots. When feasible, this type of control is very
reliable and well protected against communication and other errors.
A decentralized control in multirobot groups is desirable in many settings. For
example, it would be of much value in a “robotic” battlefield, where a continuous
centralized control from a single commander would amount to sacrificing the sys-
tem reliability and fault tolerance. The commander may give general commands
from time to time—for instance, on changing goals for the whole group or for
specific robots (which is an equivalent of prescribing each robot’s next target
position)—but most of the time the robots will be making their own motion
planning decisions.
Each robot presents a moving obstacle to other robots. (Then there may also
be static obstacles in the workspace.) There is, however, an important difference
between this situation and the situation above with arbitrary moving obstacles.
You cannot have any beforehand agreement with an arbitrary obstacle, but you
can have one with other robots. What kind of agreement would be unconstraining
enough and would not depend on shapes and dimensions and locations? The
system designers may prescribe, for example, that if two robots meet, each robot
will attempt to pass around the other only clockwise. This effectively eliminates