Automated Planning, Sensing and Control for Autonomous Underwater Robotic Systems
Date Issued
December 2019
Author(s)
Advisor
Abstract
Today’s autonomous robotic systems have a significant impact on industrial
applications and in academic disciplines. This dissertation considers a broad
range of topics, from formal methods, sensor fusion, image processing, nonlinear
control to controller synthesis of motion tasks with applications in underwater,
mobile and underground robots.
One of the most significant challenges in the robotics area lies in the area of
motion and task planning. Motion planning is the robot able to move in the
workspace while at the same time avoiding obstacles. On the other hand, task
planning refers to the robot’s ability to execute a specific task in the workspace.
The main aim is to be able for a given task in a high-level language the robot
to compile this specification into low-level descriptions in order to accomplish
a task.
Autonomous underwater robots typically have to accomplish missions in an
unknown and usually unstructured environment. The mission complexity grows
considering to limited robot sensing systems as well as the limited on-line
communications. For instance, GPS is not applicable due to the inefficient underwater
electromagnetic transmission. In addition, vision-based systems are
limited due to poor visibility in murky waters. The actuating system is usually
composed of thrusters and control surfaces; all of them have non-linear dynamics
and are strongly affected by the hydrodynamic effects. The ocean currents
and flows imply additional difficulties for the ROV control system making the
robot to deviate away from its desired state or path. Estimates of the flow velocity
provided by various sensors or techniques may be incorporated into the
control loop to compensate for the drift phenomenon. In this thesis, we address
the problem of underwater visual inspection task as a combination of (i)
a problem of localization and state estimation of the ROV with respect to the
target by fusing information from different sources; (ii) a problem of control
of an under-actuated underwater vehicle in the proximity to the target; (iii) a
problem of full coverage of fishnet cages. Autonomous multi-agent coverage of large-scale under-ground sewer networks
is also addressing in this dissertation. Sewer network systems are typically dendritic
networks converging in the downstream direction without closed loops.
In network systems theory such networks are characterized as a tree or more
precisely directed tree networks where the directionality is inherited from the
sewage flow direction. Sewer network flow channels dimensions are typically
restricted, allowing only a single inspection robot at a given position. Robots
operating in such networks can only interchange positions at channel junctions.
Wireless communications in underground sewer networks are much more challenging
than in above-ground settings. The main transmission path is through
the underground network’s channels, usually non-line-of-sight and with severe
attenuation over corridor bends and turns and there are also issues related to
multi-path reflections.
The performance of the proposed methodologies is verified in realistic simulations
in 2D and 3D virtual environments. Furthermore, extensive experimental
validation on the actual hardware was carried out in a controlled environment
at Robotics, Control, and Decision Systems (RCDS) laboratory and in the field
(open sea) under real conditions.
applications and in academic disciplines. This dissertation considers a broad
range of topics, from formal methods, sensor fusion, image processing, nonlinear
control to controller synthesis of motion tasks with applications in underwater,
mobile and underground robots.
One of the most significant challenges in the robotics area lies in the area of
motion and task planning. Motion planning is the robot able to move in the
workspace while at the same time avoiding obstacles. On the other hand, task
planning refers to the robot’s ability to execute a specific task in the workspace.
The main aim is to be able for a given task in a high-level language the robot
to compile this specification into low-level descriptions in order to accomplish
a task.
Autonomous underwater robots typically have to accomplish missions in an
unknown and usually unstructured environment. The mission complexity grows
considering to limited robot sensing systems as well as the limited on-line
communications. For instance, GPS is not applicable due to the inefficient underwater
electromagnetic transmission. In addition, vision-based systems are
limited due to poor visibility in murky waters. The actuating system is usually
composed of thrusters and control surfaces; all of them have non-linear dynamics
and are strongly affected by the hydrodynamic effects. The ocean currents
and flows imply additional difficulties for the ROV control system making the
robot to deviate away from its desired state or path. Estimates of the flow velocity
provided by various sensors or techniques may be incorporated into the
control loop to compensate for the drift phenomenon. In this thesis, we address
the problem of underwater visual inspection task as a combination of (i)
a problem of localization and state estimation of the ROV with respect to the
target by fusing information from different sources; (ii) a problem of control
of an under-actuated underwater vehicle in the proximity to the target; (iii) a
problem of full coverage of fishnet cages. Autonomous multi-agent coverage of large-scale under-ground sewer networks
is also addressing in this dissertation. Sewer network systems are typically dendritic
networks converging in the downstream direction without closed loops.
In network systems theory such networks are characterized as a tree or more
precisely directed tree networks where the directionality is inherited from the
sewage flow direction. Sewer network flow channels dimensions are typically
restricted, allowing only a single inspection robot at a given position. Robots
operating in such networks can only interchange positions at channel junctions.
Wireless communications in underground sewer networks are much more challenging
than in above-ground settings. The main transmission path is through
the underground network’s channels, usually non-line-of-sight and with severe
attenuation over corridor bends and turns and there are also issues related to
multi-path reflections.
The performance of the proposed methodologies is verified in realistic simulations
in 2D and 3D virtual environments. Furthermore, extensive experimental
validation on the actual hardware was carried out in a controlled environment
at Robotics, Control, and Decision Systems (RCDS) laboratory and in the field
(open sea) under real conditions.
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