Visual Servoing (VS) of a mobile robot requires advanced digital image
processing, and one of the techniques especially fitting for this complex
task is Image Registration (IR). In general, IR involves the geometrical
alignment of images, and it can be viewed as an optimization problem.
Therefore, we propose Metaheuristic Optimization Algorithms (MOA) for IR in
VS of a mobile robot. The comprehensive comparison study of three
state-of-the-art MOA, namely the Slime Mould Algorithm (SMA), Harris Hawks
Optimizer (HHO), and Whale Optimization Algorithm (WOA) is presented. The
previously mentioned MOA used for IR are evaluated on 12 pairs of stereo
images obtained by a mobile robot stereo vision system in a laboratory model
of a manufacturing environment. The MATLsoftware package is used for the
implementation of the considered optimization algorithms. Acquired
experimental results show that SMA outperforms HHO and WOA, while all three
algorithms perform satisfactory alignment of images captured from various
mobile robot poses.
LABORATORY MODEL OF MOBILE ROBOT WITH SECTIONAL MOVER
