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aimed to deploy cooperative multiple robot systems compatible with any robotic domain (flexible), adaptable to any
problem complexity (scalable) and qualified to respond to
failures (fault tolerant). It is based on the hybrid leader-
follower paradigm, where the execution process is distributed on each robotic system, and the deliberation process
keeps a hierarchical approach. That is, the high-level planning is locally centralized in the leader, which provides a
customized plan to every follower and sets the cooperation
with them. Also, every follower holds its own deliberative
system for the decision making process in case of a leader
failure, so they are not fully dependent. For instance, a future
Mars exploration evolved from the Mars 2020 could be a
persistent exploration mission where the Unmanned Ground
Vehicle (UGV) carries the UAV through secure locations
around the Mars surface. From those locations, the UAV
can reach scientific targets such as taking pictures of mountains' ridges or craters' interiors. This scenario can be
accomplished with a cooperative multiagent architecture
such as ARIES, where the leader would be the UGV and the
follower the UAV.
The ARIES architecture is based on the T-REX system, a goal-oriented system which follows the TeleoReactive paradigm [7]. T-REX is a multiagent architecture
to demonstrate on-board automated planning by interleaving the planning and execution processes on every agent.
It was originally deployed for oceanographic exploration,
but its general design enables its application to any
domain. The ARIES objective is to extend the T-REX
architecture to build a cooperative architecture following
the hierarchical leader-follower paradigm. This paper
describes ARIES as an initial step in demonstrating an
architecture to achieve autonomous cooperation in planetary exploration scenarios.
The rest of the paper is organized as follows. Next section, briefly explains the state of the art about autonomous
controllers for cooperative scenarios. Section "A T-REX
OVERVIEW" defines the key concepts and definitions
related to T-REX required to understand ARIES. Section
"FROM TEMPORAL ACTION-BASED TO TIMELINEBASED PLANNING" describes the planning paradigm
used by ARIES. Section "THE ARIES CONTROLLER"
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describes the ARIES architecture. Then, a study case
demonstrating the ARIES capabilities is presented in
Section "DEMONSTRATION." Finally, conclusions and
future research lines are outlined.

STATE OF THE ART
Multiple robot cooperation has experienced a notable
growth over the last two decades. Due to the advances in
robotics and artificial intelligence (AI) fields, several
approaches for robot teams have emerged, allowing those
teams to coordinate their functionalities to achieve common goals. From the point of view of the team composition, it is possible to differentiate two classes: teams of
homogeneous robots (every robot has the same functional
capabilities) or teams of heterogeneous robots (different
functional capabilities). From the point of view of the
team control, AI autonomous controllers have been
considered as a suitable approach. These controllers are
typically built interleaving deliberation and execution for
goal-oriented autonomy, providing different abstractions
for problem modeling and software framework that follows the divide-and-conquer approach. The work of
Asama et al. [8] represent an initial approach in autonomous controllers for multiple robot cooperation. It is a
distributed architecture composed of an heterogeneous
group of robotic agents, where each robotic agent is an
autonomous component with decision and communication capabilities. This paper started to consider as key
architectural features the capability to add new agents to
a system (flexible) and to adapt to any problem complexity (scalable).
A different approach is the so-called behavior-based
architectures. The main idea behind these architectures is
to emulate the behavior of basic organisms in order to
respond to single problems in a deterministic way. These
systems are rule based for enabling the stimulus-response
organic schema. In this sense, the architecture defines
context dependent rules that trigger specific behaviors.
An example of this approach is the ALLIANCE architecture [9], a behavior-based distributed architecture where

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Aerospace and Electronic Systems - March 2019

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