  The present paper aims at analyzing the topological content of the complex
trajectories that weeder-autonomous robots follow in operation. We will prove
that the topological descriptors of these trajectories are affected by the
robot environment as well as by the robot state, with respect to maintenance
operations. Topological Data Analysis will be used for extracting the
trajectory descriptors, based on homology persistence. Then, appropriate
metrics will be applied in order to compare that topological representation of
the trajectories, for classifying them or for making efficient pattern
recognition.
