Citation: Lappas, V.; Shin, H.-S.;
Tsourdos, A.; Lindgren, D.; Bertrand,
S.; Marzat, J.; Piet-Lahanier, H.;
Daramouskas, Y.; Kostopoulos, V.
Autonomous Unmanned
Heterogeneous Vehicles for Persistent
Monitoring. Drones 2022, 6, 94.
https://doi.org/10.3390/
drones6040094
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Received: 10 February 2022
Accepted: 18 March 2022
Published: 10 April 2022
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Article
Autonomous Unmanned Heterogeneous Vehicles for
Persistent Monitoring
Vaios Lappas
1,
* , Hyo-Sang Shin
2
, Antonios Tsourdos
2
, David Lindgren
3
, Sylvain Bertrand
4
,
Julien Marzat
4
, Hélène Piet-Lahanier
4
, Yiannis Daramouskas
5
and Vasilis Kostopoulos
5
1
Department of Aerospace Science & Technology, National & Kapodistrian University of Athens,
34400 Athens, Greece
2
Centre for Cyberphysical and Autonomous Systems, School of Aerospace, Transport and Management,
Cranfield University, Cranfield MK43 0AL, UK; h.shin@cranfield.ac.uk (H.-S.S.);
a.tsourdos@cranfield.ac.uk (A.T.)
3
Swedish Defence Research Agency FOI, 90621 Umea, Sweden; david.lindgren@foi.se
4
Traitement de l’Information et Systèmes, ONERA, Université Paris Saclay, 91190 Palaiseau, France;
sylvain.bertrand@onera.fr (S.B.); julien.marzat@onera.fr (J.M.); helene.piet-lahanier@onera.fr (H.P.-L.)
5
Applied Mechanics Lab, Department of Mechanical Engineering and Aeronautics, University of Patras,
26504 Patras, Greece; daramousk@ceid.upatras.gr (Y.D.); kostopoulos@upatras.gr (V.K.)
* Correspondence: valappas@aerospace.uoa.gr
Abstract:
Swarms of unmanned vehicles (air and ground) can increase the efficiency and effectiveness
of military and law enforcement operations by enhancing situational awareness and allowing the
persistent monitoring of multiple hostile targets. The key focus in the development of the enabling
technologies for swarm systems is the minimisation of uncertainties in situational awareness infor-
mation for surveillance operations supported by ‘system of systems’ composed of static and mobile
heterogeneous sensors. The identified critical enabling techniques and technologies for adaptive,
informative and reconfigurable operations of unmanned swarm systems are robust static sensor
network design, mobile sensor tasking (including re-allocation), sensor fusion and information fusion,
including behaviour monitoring. The work presented in this paper describes one of the first attempts
to integrate all swarm-related technologies into a prototype, demonstrating the benefits of swarms
of heterogeneous vehicles for defence applications used for the persistent monitoring of high-value
assets, such as military installations and camps. The key enabling swarm system technologies are
analysed here, and novel algorithms are presented that can be implemented in available COTS-based
unmanned vehicles. The algorithms have been designed and optimised to require small computa-
tional power, be flexible, be reconfigurable and be implemented in a large range of commercially
available unmanned vehicles (air and ground).
Keywords: unmanned systems; persistent monitoring; autonomy
1. Introduction
Advances in microelectronics, UAV development, autonomous systems and guidance,
navigation and control systems have enabled the development of unmanned vehicles to
perform complex missions, such as surveillance and persistent monitoring tasks. These au-
tonomous systems, mostly operated in small groups, are able to deliver significant amounts
of data in real time; however, they are constrained by the levels of autonomy available and
the difficulties of integrating multiple vehicles in swarms. Multiple unmanned vehicles can
add not only strength in numbers, but unique capabilities in redundancy, mission flexibility
and target tracking/monitoring which can enhance mission capabilities for defence and
law enforcement needs. Asymmetrical warfare and the need to simultaneously detect
unidentified targets with multiple behaviours are challenging current autonomous systems,
as a single, yet capable UAV is not necessarily able to detect, track and persistently monitor
Drones 2022, 6, 94. https://doi.org/10.3390/drones6040094 https://www.mdpi.com/journal/drones
