Co-advisor: Rogelio LOZANO
Grant from french Government
Date PhD finished: December 4th, 2015
Current position: Postdoctoral position, USA
The present document addresses, theoretically and experimentally, the most relevant topics
for Unmanned Aerial Vehicles (UAVs) in autonomous and semi-autonomous navigation.
According with the multidisciplinary nature of the studied problems, a wide range of
techniques and theories are covered in the fields of robotics, automatic control, computer
science, computer vision and embedded systems, among others.
As part of this thesis, two different experimental platforms were developed in order to
explore and evaluate various theories and techniques of interest for autonomous navigation.
The first prototype is a quadrotor specially designed for outdoor applications and was fully
developed in our lab. The second testbed is composed by a non expensive commercial
quadrotor kind AR. Drone, wireless connected to a ground station equipped with the Robot
Operating System (ROS), and specially intended to test computer vision algorithms and
automatic control strategies in an easy, fast and safe way.
In addition, this work provides an study of data fusion techniques looking to enhance
the UAVs pose estimation provided by commonly used sensors. Two strategies are evaluated
in particular, an Extended Kalman Filter (EKF) and a Particle Filter (PF). Both estimators
are adapted for the system under consideration, taking into account noisy measurements
of the UAV position, velocity and orientation. Simulations show the performance of
the developed algorithms while adding noise from real GPS (Global Positioning System)
Safe and accurate navigation for either autonomous trajectory tracking or haptic teleoperation
of quadrotors is presented as well. A second order Sliding Mode (2-SM) control
algorithm is used to track trajectories while avoiding frontal collisions in autonomous flight.
The time-scale separation of the translational and rotational dynamics allows to design position
controllers by giving desired references in the roll and pitch angles, which is suitable
for quadrotors equipped with an internal attitude controller. The 2-SM control allows to
add robustness to the closed-loop system and attenuates the chattering effect. A Lyapunov
based analysis probes the system stability. Vision algorithms are employed to estimate the
pose of the vehicle using only a monocular SLAM (Simultaneous Localization and Mapping)
fused with inertial measurements. Distance to potential obstacles is detected and
computed using the sparse depth map from the vision algorithm. For teleoperation tests,
a haptic device is employed to feedback information to the pilot about possible collisions,
by exerting opposite forces. The proposed strategies are successfully tested in real-time
experiments, using a low-cost commercial quadrotor.
Also, conception and development of a Micro Aerial Vehicle (MAV) able to safely
interact with human users by following them autonomously, is achieved in the present
work. Once a face is detected by means of a Haar cascade classifier, it is tracked applying
a Kalman Filter (KF), and an estimation of the relative position with respect to the face
is obtained at a high rate. A linear Proportional Derivative (PD) controller regulates the
UAV’s position in order to keep a constant distance to the face, employing as well the extra
available information from the embedded UAV’s sensors. Several experiments were carried
out through different conditions, showing good performance even under disadvantageous
scenarios like outdoor flight, being robust against illumination changes, wind perturbations,
image noise and the presence of several faces on the same image.
Finally, this thesis deals with the problem of implementing a safe and fast transportation system using an UAV kind quadrotor with a cable suspended load. The objective consists in transporting the load from one place to another, in a fast way and with minimum swing in the cable. An Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) for the system of interest is successfully implemented and tested in real time experiments. The use of this control technique avoids the use of an extra sensor for the swing angle measurement. An experimental platform composed by a quadrotor equipped with a rigid rod with two degrees of freedom in the joint, is developed. UAV navigation is achieved via monocular vision.