  Control of systems of automated guided vehicles involves action planning at
many levels. For efficient control of these systems, accurate estimation of
cost parameters (speed, energy, task completion performance, \textit{et~cetera}
is required. These parameters change along time, particularly in
battery-operated robots, which are very sensitive to battery level variations.
This work addresses the problem of on-line cost parameter identification and
estimation for proper control decisions of the individual mobile robots and for
the system as a whole. Several filtering and estimation methods have been
investigated with respect to travelling times, which are dramatically affected
by battery charges and condition of facility's floors, among other factors.
Results show that these parameters depend on the robot, the route and the
moment, so they are linked to a particular robot, a region of the floor and a
time period (or to a battery level). Moreover, differences with static,
pre-runtime travelling time computations, either heuristically or by
characterization of real robots, are large enough to affect to system's
performance and overall productivity and efficiency.

Robotics