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Ongoing work is committed to the refinement of the
domain model towards a higher degree of realism, in
view of a fully dynamic exploitation of the proposed
Representation & Reasoning techniques in a SensePlan-Act loop experimental setting.
tool. Subsequently, we carried out an empirical evaluation,
and demonstrated our solving algorithm's performances in
providing good quality solutions, by efficiently taking into
account all the most significant problem constraints, in particular those related to energy management. We also demonstrated that significant solution quality improvement can be
provided by our makespan-optimization framework in a relatively small amount of time.
The contents of this paper describe an ongoing work.
More activities are currently being carried out in many
directions, like the refinement of the terrain model to take
into account characteristics such as slope, compactness,
roughness, etc., in view of a fully dynamic utilization of the
scheduling engine in a simulated Sense-Plan-Act loop execution context. It was outside the scope of this paper to
present the preliminary results of such experimentation.
The interested reader may refer to [23] for more information on the current state of activities.
As a future research path, we find very interesting considering different space exploration scenarios where groups of
autonomous rovers are in charge of collaborating on the fulfilment of the specific mission goals. This kind of problem
domains that involve the synchronization of multiple agents, are
naturally addressed through the application of Computational
Intelligence (CI) techniques based on decentralized approaches, in
contrast to centralized solutions like the one presented in this
work. There are many outstanding examples in literature where
distributed methods have been successfully applied to solve
real-world problems. For instance, in Li et al [24], a multi-agent
system is proposed to tackle the service restoration problem in
power distribution networks; while in Abielmona et al [25], a
novel agent-based architecture is proposed for territorial or
perimeter-security applications.
Acknowledgment

Daniel Diaz is supported by the European Space Agency
(ESA) under the Networking and Partnering Initiative (NPI)
Autonomy for Interplanetary Missions (ref. 2169/08/NI/PA).
The authors are grateful for all the support obtained through
ESA-ESTEC, specially from its ESA's technical officer
Mr. Michel Van Winnendael. M.D. R-Moreno is funded by
the CDTI project COLSUVH.
References

[1] T. Estlin, D. Gaines, C. Chouinard, R. Castano, B. Bornstein, M. Judd, I. Nesnas,
and R. Anderson, "Increased Mars Rover autonomy using AI planning, scheduling and
execution," in Proc. IEEE Int. Conf. Robotics Automation, 2007, pp. 4911-4918.

24

IEEE ComputatIonal IntEllIgEnCE magazInE | novEmbEr 2013



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