Part B | 17.6
414 Part B Autonomous Ocean Vehicles, Subsystems and Control
17.6 Underwater Autonomous Manipulation
Autonomous manipulation on a moving base, such
as terrestrial mobile robots, humanoids, and underwater robotic vehicles, is a very challenging task in the
area of robotics in general, especially in unstructured
environments, such as underwater. It refers to the capability of a robot system that performs intervention
tasks requiring physical contact with unstructured environments without continuous human supervision. Unlike industrial manipulators having fixed bases on the
floor, autonomous manipulation requires a system capable of assessing a situation, including self-calibration
based on sensory information, and executing or revising a course of manipulating action without continuous
human intervention. Therefore, developing a system
capable of fully autonomous manipulation would be
a great achievement and make a substantial impact on
a variety of application areas with significant economical, societal, and scientific importance [17.71].
Let us look at one scenario of cutting an underwater cable. With given information about the cable’s
location and shape, the vehicle has to navigate to the
location, identify the cable, position itself, and cut the
cable. It may sound like a very simple task. However,
it would not be so simple if it has to be done in autonomous mode. Even in teleoperation mode, it would
not be an easy task without the coordinated motion control if the vehicle is floating in water. In fact, the low
bandwidth and significant time delay inherent in acoustic subsea communications represent a considerable
obstacle to remotely operate a manipulation system,
making it impossible for remote controllers to react
to problems in a timely manner. Nevertheless, robots
for autonomous underwater intervention would pave
the way for a different range of new operations, such
as deep-ocean and under-ice exploration, tasks in hazardous areas, tasks in natural or man-made disastrous
regions, automated searches, surveillance missions, to
name a few.
In the past, many researchers have studied advanced control of AUV itself as reported by Carreras et al. [17.72, 73], Zhao and Yuh [17.74], Hanai
et al. [17.75], Kim and Yuh [17.76], Lee et al. [17.77],
Yuh and Nie [17.78], and Yang et al. [17.79], but
only a few AUVs with manipulators were introduced.
OTTER is an AUV equipped with a single degreeof-freedom arm, which was designed to be used as
a testbed for autonomous technologies at the Stanford
Aerospace Robotics Lab. in 1996. It is a hoveringcapable underwater vehicle, which operates in a test
tank at the Monterey Bay Aquarium Research Institute (MBARI). Various research topics were studied with OTTER, including precise, high-speed underwater manipulators, task-level programming with
an advanced finite-state machine paradigm, underwater
video navigation, station-keeping, tracking, and automatic objects retrieval [17.80]. Another interventionAUV (I-AUV), namely Autonomous Light Intervention
Vehicle (ALIVE), was developed by Cybernetix in
2003. The aim of the EU-funded ALIVE project was
to develop an intervention-I-AUV capable of docking
to a subsea structure, which has not been specifically
modified for AUV use. A description of the ALIVE vehicle was given by Evans et al. [17.81]. The most recent
effort in developing an AUV for intervention missions
is the TRIDENT FP7 EU research project funded by
the European Commission for 3 years, since March
2010. The consortium is made up of eight partners: Universitat Jaume-I, University of Girona, University of
the Balearic Islands, University of Bologna, University
of Genova, Heriot-Watt University and Instituto Superior Tecnico, and company Graal Tech. The long-term
objective of the project is the design and implementation of a new methodology enabling multipurpose
underwater intervention missions with a very high autonomy level [17.82–84]. A team of two cooperative
heterogeneous robots with complementary skills, an autonomous surface craft (ASC) and an intervention-AUV
(I-AUV) endowed with a dexterous manipulator, are
used to perform underwater manipulation tasks. The
proposed methodology is based on two steps. First, the
I-AUV cooperates with the ASC performing path to
survey an area of interest, gathering opto/acoustic data
from the seafloor. During this phase, the I-AUV performs accurate path following and terrain tracking, to
maximize bottom coverage and data quality. The motion of the ASC is coordinated with that of the I-AUV to
achieve precise USBL (ultra short base line) positioning
and reliable acoustic communications. After the survey,
a multimodal two-and-a-half-dimensional (2.5-D) elevation map of the environment is built consisting on
a photomosaic rendered over an accurate bathymetric
map, both being jointly and globally optimized. At the
second step, I-AUV is launched to search for an object of interest manually selected by the user over the
constructed map. When the object (the target of the
intervention) is found, the I-AUV switches to free floating navigation mode. An optimization algorithm is used
to decide how to move the arm, the vehicle, or both
together in order to satisfy a set of constraints, such
as keeping the object within the camera FOV, keeping a desired altitude, and avoiding arm singularities.
The manipulation of the object takes place through
a dexterous three-fingered hand attached to a redundant
robot arm (7 DOF) and assisted with proper percep-
414 Part B Autonomous Ocean Vehicles, Subsystems and Control
17.6 Underwater Autonomous Manipulation
Autonomous manipulation on a moving base, such
as terrestrial mobile robots, humanoids, and underwater robotic vehicles, is a very challenging task in the
area of robotics in general, especially in unstructured
environments, such as underwater. It refers to the capability of a robot system that performs intervention
tasks requiring physical contact with unstructured environments without continuous human supervision. Unlike industrial manipulators having fixed bases on the
floor, autonomous manipulation requires a system capable of assessing a situation, including self-calibration
based on sensory information, and executing or revising a course of manipulating action without continuous
human intervention. Therefore, developing a system
capable of fully autonomous manipulation would be
a great achievement and make a substantial impact on
a variety of application areas with significant economical, societal, and scientific importance [17.71].
Let us look at one scenario of cutting an underwater cable. With given information about the cable’s
location and shape, the vehicle has to navigate to the
location, identify the cable, position itself, and cut the
cable. It may sound like a very simple task. However,
it would not be so simple if it has to be done in autonomous mode. Even in teleoperation mode, it would
not be an easy task without the coordinated motion control if the vehicle is floating in water. In fact, the low
bandwidth and significant time delay inherent in acoustic subsea communications represent a considerable
obstacle to remotely operate a manipulation system,
making it impossible for remote controllers to react
to problems in a timely manner. Nevertheless, robots
for autonomous underwater intervention would pave
the way for a different range of new operations, such
as deep-ocean and under-ice exploration, tasks in hazardous areas, tasks in natural or man-made disastrous
regions, automated searches, surveillance missions, to
name a few.
In the past, many researchers have studied advanced control of AUV itself as reported by Carreras et al. [17.72, 73], Zhao and Yuh [17.74], Hanai
et al. [17.75], Kim and Yuh [17.76], Lee et al. [17.77],
Yuh and Nie [17.78], and Yang et al. [17.79], but
only a few AUVs with manipulators were introduced.
OTTER is an AUV equipped with a single degreeof-freedom arm, which was designed to be used as
a testbed for autonomous technologies at the Stanford
Aerospace Robotics Lab. in 1996. It is a hoveringcapable underwater vehicle, which operates in a test
tank at the Monterey Bay Aquarium Research Institute (MBARI). Various research topics were studied with OTTER, including precise, high-speed underwater manipulators, task-level programming with
an advanced finite-state machine paradigm, underwater
video navigation, station-keeping, tracking, and automatic objects retrieval [17.80]. Another interventionAUV (I-AUV), namely Autonomous Light Intervention
Vehicle (ALIVE), was developed by Cybernetix in
2003. The aim of the EU-funded ALIVE project was
to develop an intervention-I-AUV capable of docking
to a subsea structure, which has not been specifically
modified for AUV use. A description of the ALIVE vehicle was given by Evans et al. [17.81]. The most recent
effort in developing an AUV for intervention missions
is the TRIDENT FP7 EU research project funded by
the European Commission for 3 years, since March
2010. The consortium is made up of eight partners: Universitat Jaume-I, University of Girona, University of
the Balearic Islands, University of Bologna, University
of Genova, Heriot-Watt University and Instituto Superior Tecnico, and company Graal Tech. The long-term
objective of the project is the design and implementation of a new methodology enabling multipurpose
underwater intervention missions with a very high autonomy level [17.82–84]. A team of two cooperative
heterogeneous robots with complementary skills, an autonomous surface craft (ASC) and an intervention-AUV
(I-AUV) endowed with a dexterous manipulator, are
used to perform underwater manipulation tasks. The
proposed methodology is based on two steps. First, the
I-AUV cooperates with the ASC performing path to
survey an area of interest, gathering opto/acoustic data
from the seafloor. During this phase, the I-AUV performs accurate path following and terrain tracking, to
maximize bottom coverage and data quality. The motion of the ASC is coordinated with that of the I-AUV to
achieve precise USBL (ultra short base line) positioning
and reliable acoustic communications. After the survey,
a multimodal two-and-a-half-dimensional (2.5-D) elevation map of the environment is built consisting on
a photomosaic rendered over an accurate bathymetric
map, both being jointly and globally optimized. At the
second step, I-AUV is launched to search for an object of interest manually selected by the user over the
constructed map. When the object (the target of the
intervention) is found, the I-AUV switches to free floating navigation mode. An optimization algorithm is used
to decide how to move the arm, the vehicle, or both
together in order to satisfy a set of constraints, such
as keeping the object within the camera FOV, keeping a desired altitude, and avoiding arm singularities.
The manipulation of the object takes place through
a dexterous three-fingered hand attached to a redundant
robot arm (7 DOF) and assisted with proper percep-