
Abstract
The problem of this thesis concerns the control of the movements and the equilibrium of hu-
manoid robots that have a mobile base with omnidirectionnal wheels. The developed methods aim
to reach high dynamical performances for this type of robot, while ensuring it stability and equili-
brium.
Humanoid robots have generally a center of mass relatively high compared to its contact surface
with the ground. Therefore, the slightest acceleration of the robot bodies induces a large variation
of the distribution of the contact forces with the ground. If they are not properly controlled, the
robot can fall. Moreover, the robot having a mobile base with wheels, a disturbance can easily
bring it to tilt on two wheels. Finally, a specific interest have been provided about the realisation
of a real time controler implemented on the embedded system of the robot. This implies some
constraints about the computationnal time of the control law.
In order to answer these problems, two linear models of the robot have been developed. The
first allows to modelize the dynamics of the robot when it has all of its wheels in contact with the
ground. The second allows to modelize the dynamics of the robot when it tilts on two of its wheels.
These models have been developed by taking into account the mass distribution of the robot.
These models have been subsequently used in two predictive control laws, allowing to take into
account at every instant the dynamical constraints as weel as the future behavior of the robot. The
first allows to control the movements of the robot when it has all of its wheels in contact with the
ground, preventing it for tilting. The second allows the robot to recover itself in a situation when a
disturbance bring it to tilt, in order to bring back all of its wheels in contact with the ground.
Also, a supervisor that has a state machine has been made in order to define which control law
has to be executed at each instant. This supervisor uses the available sensors on the robot in order
to observe its tilt state.
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