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6.2.1

Swarm-inspired Cooperative Search

The cooperative search operation of multiple UAVs is implemented in two scenarios of target

detection – single target detection and multiple target detection. Each scenario is evaluated

with two performance criteria: the average detection time and the number of targets located

within the maximum time length (all-located target detection). The number of UAVs and the

number of targets are the two variables used to implement the experiments. The experiments

are setup with different combinations of UAVs and targets, which alters one of the variables

while the other remains unchanged. The experimental data suggest that given the same

numbers of UAVs and the same numbers of targets, the diagonal formation of two UAVs

consumed much less detection time in average and was able to successfully locate all the

targets within the maximum time length in all but one experimental run for the 20 UAVs / 5

targets combination. The triangular formation of three UAVs consumed longer detection time

on average and was unable to locate all the targets within the maximum time length. The

results of t-test also indicate that in all combinations of targets/UAVs, the two-UAV

formation significantly outperforms the three-UAV formation.

For three-UAV formation, it takes time to engage three UAVs to converge onto the initial

detection of target signal. The performance is significantly constrained by the number of

UAVs available at the time of generating formation. Once the target signal is initially

detected, the detecting UAV needs to recruit two other UAVs. In particular, when there is

only a limited number of UAVs, it would take much longer time for the detecting UAV to

find qualified UAVs to recruit. Additionally, when there are more targets to be detected, a

170 prolonged detection time on average, as well as reduced number of located targets within the

maximum time length.

6.2.2

Comparison with Current Approaches of Cooperative

Search

The swarm-inspired search strategy proposes to accomplish the cooperative search of UAVs

through the following mechanisms: random search pattern of individual UAVs, signal-

stimulated communications, recruitment and convergence, and the generation and

maintenance of flight formations of UAVs. Table 6.6 below outlines the context and features

each for the swarm-inspired search strategy and existing approaches of the cooperative search

of UAVs.

Table 6.6 The Cooperative Control Architecture and Swarm-inspired Search Strategy

The Cooperative Control

Architecture Swarm-inspired Search Strategy

4-State Control Architecture (Pack and York 2005; York, Pack et al. 2007): Global Search, Approach located Target, Orbit and Locate Target, Local Search for lost mobile Target.

Behaviour-based Search Mechanisms:

Random Search Pattern of Individual UAVs, Signal- stimulated Communications, Recruitment, Emergence of Flight Formations, Synchronised Circling.

Detecting and Locating targets with sensing and image processing techniques, e.g.:

1) The Line Formation (Vincent and Rubin 2004; Altshuler, Yanovsky et al. 2008);

2) The Triangulation of Multiple UAVs (Toussaint, De Lima et al. 2007; Pack, DeLima et al. 2009)

Flight Formations of UAVs:

1) Diagonal Formation of Two UAVs; 2) Triangular Formation of Three UAVs.

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The Line Formation (Vincent and Rubin 2004; Altshuler, Yanovsky et al. 2008): Pre-defined with fixed number of UAVs in the formation pattern;

Require prior knowledge of the search area;

Search and locate mobile targets with parallel sweep pattern;

Diagonal/Triangular Formation of UAVs:

Any of the two/three UAVs are able to converge onto cooperative formations;

The initial detection of target signal stimulates the communications and recruitment between UAVs; The formation is generated on an ad hoc basis and no advanced information of the search area is required; UAVs retain the formation and circle synchronously to track and locate the mobile target.

The Triangulation of Multiple UAVs (Toussaint, De Lima et al. 2007; Pack, DeLima et al. 2009):

With two UAVs, the target location is estimated by the intersection of the two angle bearing lines of UAVs;

With three UAVs, the target location is estimated in the centre of the

triangulation.

Diagonal/Triangular Formation of UAVs: The target location can be identified at unique

coordinates within the overlapping sensor coverage of UAVs;

Synchronised circling behaviour enables UAVs to track the target movement and locate the target in a wider area.

The line formation of UAVs is predefined and consists of a fixed number of UAVs (Vincent

and Rubin 2004). It requires UAVs to be aware of the search area in advance and hence

demands basic but accurate information to be provided before initiating the search operation.

This involves additional ground work beforehand and is not robust enough to be adaptable

with different conditions of search area. In the case of UAV failure, retaining the original

formation pattern with no new UAVs joining in could also reduce the detection coverage of

the UAV formation. Reduced detection coverage is likely to cause extra time consumption

and less efficiency of target detection. Additionally, although the parallel sweep pattern (both

the original sweep pattern (Vincent and Rubin 2004) and the angled sweep pattern (Altshuler,

Yanovsky et al. 2008)) is able to fully cover the entire search area from one end of the field to

172 one side of the search field; and the effectiveness and efficiency may also be constrained to

the size and shape of the search field.

The triangulation of UAVs engages a team of two and/or three UAVs to locate the target with

their angle-to-target estimations (Pack and York 2005; Toussaint, De Lima et al. 2007; Pack,

DeLima et al. 2009). However, the estimated target locations have various deviations from

the actual target locations. Also, the leader-follower approach coordinates UAVs to join the

formation but in the mean time, it requires additional calculations of the followers‟ trajectories and reliable angle-to-target estimations can only be produced when all

cooperating UAVs are in a stabilised orbit.

The swarm-inspired search strategy proposes behaviour-based mechanisms that assign UAVs

with identical rules of behaviour. Stimulated by the initial detection of target signal, the

cooperative flight formations are generated between any of the two and/or three UAVs. No

advanced information of the search area is needed as the UAV formations are generated on

an ad hoc basis, and are only taking place when there is a target signal detected. In this way,

other UAVs are able to explore different parts of the search area, and thus to enhance

detection effectiveness of UAVs. The diagonal formation of two UAVs and the triangular

formation of three UAVs generate overlapping sensor coverage in order to track and locate

the mobile target. Instead of estimating the target location, the goal is to locate the target at

unique coordinates in the overlapping sensor coverage of UAVs. If UAVs are unable to

identify the target location via the formation initially, they then circle around together while

retaining the formation pattern intending to track the target in a wider area. The cooperative

formations of UAVs are emerged from randomised individual detection of target signal via

signal-stimulated communications. Such kind of mechanisms increases robustness and

efficiency of target detection, and enables UAVs to effectively respond to various conditions

173 The experimental results indicate that the swarm-inspired search strategy has delivered

promising performance of searching for multiple mobile targets. The behaviour-based search

mechanisms enable UAVs to explore the search area in a dynamic pattern. The two formation

patterns of UAVs are able to achieve the unique coordinates of targets and accomplish the

search operation effectively in terms of both detection accuracy and time consumption. The

diagonal formation of two UAVs has outperformed the triangular formation of three UAVs

with very significantly lower time of detection on average and the number of located targets

within the maximum time length. Thus, it is shown that, with appropriate formations, an

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