Abstract:
This paper describes the navigation of a two-wheel
drive mobile robot along a predefined path under uneven road
conditions where it cannot solely rely on encoders, GPS or an
accelerometer individually. There are conditions when low
friction or slippery ground surfaces such as sandy paths and
pits cause one or both encoders to halt or rotate less as the robot
moving forward. Areas covered with clouds, trees or structures
can block GPS signals. Sudden pickups and halts give false
information from accelerometers. Therefore Kalman filter
based sensor fusion algorithm is implemented in order to get
the best position estimation for the mobile robot using above
sensor outputs. The Special feature of this algorithm is that it
includes a simple method to overcome the effects of encoder
errors due to the slipping of wheels of the mobile robot, which
does not require complex computations to additional
measurement units to directly measure the slipping of the
wheels of the robot. Finally the validity of the proposed
algorithm is demonstrated via simulation.
