838 research outputs found
Considerations on the electronic control system for autonomous underwater vehicle
Get PDFPeer Reviewe
Power system of the Guanay II AUV
Get PDFGuanay
II
is
an
autonomous
underwater
vehicle
(AUV)
designed
to
perform
measurements
in
a
water
column.
In
this
paper
the
aspects
of
the
vehicle’s
power
system
are
presented
with
particular
focus
on
the
power
elements
and
the
state
of
charge
of
the
batteries.
The
system
performs
both
measurement
and
monitoring
tasks
and
also
controls
the
state
of
charge
(SoC)
of
the
batteries.
It
allows
simultaneous
charging
of
all
batteries
from
outside
the
vehicle
and
has
a
wireless
connection/disconnection
mode.
Guanay
II
uses
a
NiCd
battery
and
for
this
reason
the
current
integration
as
a
SoC
methodology
has
been
selected.
Moreover,
it
has
been
validated
that
it
is
possible
to
obtain
instant
consumption
from
the
SoC
circuit.
Finally,
laboratory
and
vehicle
navigation
tests
have
been
performed
to
validate
the
correct
operation
of
the
systems
and
the
reliability
of
the
measured
dataPostprint (published version
Development of a control system for an autonomous underwater vehicle
Get PDFThis work proposes the development of a control
system for an autonomous underwater vehicle dedicated to the
observation of the oceans. The vehicle, a hybrid between
Autonomous Underwater Vehicles (AUVs) and Autonomous
Surface Vehicles (ASV), moves on the surface of the sea and
makes vertical immersions to obtain profiles of a water column,
according to a pre-established plan. The displacement of the
vehicle on the surface allows the navigation through GPS and
telemetry communication by radio-modem. The vehicle is
2300mm long by 320mm wide. It weighs 85kg and reaches a
maximum depth of 30m. A control system based on an embedded
computer is designed and developed for this vehicle that allows a
vehicle's autonomous navigation. This control system has been
divided into navigation, propulsion, safety and data acquisition
subsystems.Peer ReviewedPostprint (author’s final draft
TransfQMix: transformers for leveraging the graph structure of multi-agent reinforcement learning problems
Get PDFCoordination is one of the most difficult aspects of multi-agent reinforcement learning (MARL). One reason is that agents normally choose their actions independently of one another. In order to see coordination strategies emerging from the combination of independent policies, the recent research has focused on the use of a centralized function (CF) that learns each agent's contribution to the team reward. However, the structure in which the environment is presented to the agents and to the CF is typically overlooked. We have observed that the features used to describe the coordination problem can be represented as vertex features of a latent graph structure. Here, we present TransfQMix, a new approach that uses transformers to leverage this latent structure and learn better coordination policies. Our transformer agents perform a graph reasoning over the state of the observable entities. Our transformer Q-mixer learns a monotonic mixing-function from a larger graph that includes the internal and external states of the agents. TransfQMix is designed to be entirely transferable, meaning that same parameters can be used to control and train larger or smaller teams of agents. This enables to deploy promising approaches to save training time and derive general policies in MARL, such as transfer learning, zero-shot transfer, and curriculum learning. We report TransfQMix's performances in the Spread and StarCraft II environments. In both settings, it outperforms state-of-the-art Q-Learning models, and it demonstrates effectiveness in solving problems that other methods can not solve.This project has received funding from the EU’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 893089. This work acknowledges the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S). We gratefully acknowledge the David and Lucile Packard Foundation.Peer ReviewedPostprint (author's final draft
Design of obstacle detection and avoidance system for GUANAY II AUV
Get PDFPostprint (published version
Linear control of the yaw and rudder limitations
Get PDFThis work presents a detailed situation about the linear control design for the yaw in the Cormoran autonomous underwater vehicle (auv). The development includes the physical limitations of the rudder that involve more constraints for the control.
The whole system is simulated in simulink and three different controls (P, PD, PID) are compared.Postprint (published version
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