چکیده (انگلیسی):

Autonomous navigation for a mobile robot still remains as a challenging area to be explored. In an
indoor environment, while GPS is unavailable and wheel encoder suffer from error accumulation due
to wheel slips, vision-based travelled distance estimation can be considered as an alternative approach
for more accurate measurements. This study presents a new algorithm to estimate travelled distance of
the mobile robot in an indoor environment. Using a downward looking camera, features points are
detected from the floor texture and tracked with the Lucas-Kanade optical flow technique. The
measurement accuracy of this algorithm will be put through several experiments on real scenarios
which involve comparing the proposed techniques, running the algorithm on different type of indoor
surface at different speed and different trajectories.