Method and system for managing a fleet of unmanned machines

Abstract

The invention relates to a method for managing a fleet of unmanned machines (5) by means of a computer system (1) comprising a supervisor (2) connected to a user interface (3) and to a missions manager (4) which controls the movements of the machines. The invention also relates to a computer system (1) implementing such a method.

Description

DESCRIPTION TITLE: Method and system for managing a fleet of unmanned vehicles Technical field of the invention

[0001] The present invention relates to the field of systems for managing the movement of unmanned vehicles, in particular drones. The invention relates in particular to a method for managing a fleet of unmanned vehicles by means of a computer system comprising a supervisor connected to a user interface and to a mission manager which controls the movements of the vehicles. The invention also relates to a computer system implementing such a method. The invention applies to unmanned vehicles, such as, for example, rolling or flying drones, in particular those used for carrying out inventories within logistics environments. State of the prior art

[0002] The management of unmanned vehicle movements is traditionally carried out manually and individually, i.e. a user manages the movements of a single vehicle using a remote control system, composed for example of a remote control and a virtual headset. However, some applications require the use of a fleet of vehicles and, in this case, the movements of each vehicle can no longer be managed manually and individually. However, when it comes to managing the movements of not just a single unmanned vehicle but a fleet of vehicles, the management systems we know are those that allow the management of the movements of a fleet of drones used for the implementation of sound and light shows or pyrotechnics.However, these systems allow for the management of drone movements in a basic way only, in that they are limited to allowing the specification of trajectories that are taken into account to manage the movements of each drone. On the other hand, no known system allows for more detailed management of the machines, particularly when it comes to taking into account. different types of missions that one wishes to accomplish with a fleet of vehicles, for example in the context of carrying out inventories within logistics environments or for military applications. For example, no known system allows the automated allocation of vehicles in a fleet to one or more missions that one wishes to accomplish. Summary of the invention

[0003] The invention aims to overcome these shortcomings. In particular, it aims to provide a method and a system that allow a user to remotely manage a fleet of unmanned vehicles, in particular according to missions to be accomplished. The invention also aims to enable the management of a fleet of vehicles that can adapt in real time the allocation of vehicles in the fleet for the accomplishment of one or more missions, in particular according to possible failures of the vehicles or new specified missions. The invention also aims to enable the management of a fleet of vehicles that are not identical in terms of their attributes. The invention also aims to provide a system that provides security means to ensure at all times that the management of a fleet of vehicles is operational. The invention thus aims to enable the remote management of a fleet of unmanned vehicles in a more advanced manner than known systems.

[0004] In order to achieve these objectives, the invention relates, according to a first aspect and a first embodiment, to a method for managing a fleet of unmanned vehicles by means of a computer system comprising a supervisor connected to a user interface and to a mission manager which controls the movements of the vehicles, the method comprising the steps of: • a first step of obtaining by the supervisor at least data characterizing a first mission specified by means of the user interface; • a second stage of determination by the supervisor, based at least on the data obtained during the first stage, of data characterizing a first set of possible fleet allocations to accomplish the first mission; • a third step of determination by the supervisor, for several allocations of the first set of possible allocations of the fleet, of at least data characterizing a first value of quality of accomplishment of the first mission and data characterizing a first value of the risk of not being able to accomplish one or more additional missions; • a fourth stage of determination by the supervisor, based on the data determined during the third stage, of at least a first specific allocation of the fleet to accomplish the first mission; • a fifth step of transmission by the supervisor of data characterizing a first selected allocation of the fleet to accomplish the first mission to the mission manager; and • a sixth stage of control by the mission manager of the movements of the machines based on the data characterizing a first allocation selected from the fleet to accomplish the first mission.

[0005] According to one embodiment, the method may comprise the following steps: • a seventh step of obtaining by the supervisor at least data characterizing a second mission specified by means of the user interface or based on a detection carried out by a machine; • an eighth stage of determination by the supervisor, based at least on the data obtained during the first stage and the seventh stage, of data characterizing a second set of possible allocations of the fleet to accomplish the first and second missions; • a ninth step of determination by the supervisor, for several allocations of the second set of possible allocations of the fleet, at least data characterizing a second value of quality of completion of the first mission, data characterizing a value of quality of completion of the second mission and data characterizing a second value of the risk of not being able to accomplish one or more additional missions; • a tenth stage of determination by the supervisor, based on the data determined during the ninth stage, of at least a second particular allocation of the fleet to accomplish the first and second missions; • an eleventh step of transmission by the supervisor of data characterizing a second selected allocation of the fleet to accomplish the first and second missions to the mission manager; and • a twelfth stage of control by the mission manager of the movements of the machines according to the data characterizing a second allocation selected from the fleet to accomplish the first and second missions.

[0006] Alternatively, the fifth and eleventh steps may be performed based on input made through the user interface.

[0007] According to another variant, the data characterizing a first mission and the data characterizing a second mission may contain data characterizing a mission type parameter and data characterizing a mission priority parameter.

[0008] According to yet another variant, the second and eighth steps can be carried out based on data characterizing an attribute or a failure of a machine.

[0009] According to yet another variant, the third, fourth, ninth and / or tenth step can be carried out by considering a time horizon parameter pre-established or specified by means of the user interface.

[0010] According to yet another variant, the third step may comprise a step of determining data characterizing a value of a priority parameter of the first mission and / or the ninth step may comprise a step of determining data characterizing a value of a priority parameter of the second mission.

[0011] According to yet another variant, the data characterizing a first value of quality of completion of the first mission, the data characterizing a second value of quality of completion of the first mission and the data characterizing a value of quality of completion of the second mission can be determined as a function of a value of duration of completion of a mission considered, of a value of quality of perception by means of detection devices on board the machines, of a value of a ratio between the sum of the surfaces covered by the machines and the surface of a geographical zone specified by means of the user interface and / or of a value of the autonomy of a machine with regard to the geographical zone.

[0012] According to yet another variant, the data characterizing a first value of the risk of not being able to accomplish one or more additional missions and the data characterizing a second value of the risk of not being able to accomplish one or more additional missions can be determined as a function of a probability value which depends on a number of devices necessary to accomplish the additional mission(s).

[0013] According to another embodiment, the method may comprise a thirteenth step of verification by the supervisor of its connectivity with the mission manager and with the user interface.

[0014] According to a second aspect, the invention relates to a device for managing a fleet of unmanned vehicles, the system comprising a supervisor connected to a user interface and a mission manager which jointly implement a process as described above. Brief description of the figures

[0015] Other characteristics and advantages of the invention will appear on examining the detailed description below, and the appended figures, in which:

[0016] [Fig. 1] is a schematic illustration of a system according to the invention;

[0017] [Fig. 2] is a flowchart of the steps of a method according to a first embodiment of the invention;

[0018] [Fig. 3] is a flowchart of certain steps of a method according to a second embodiment of the invention; and

[0019] [Fig. 4] is a flowchart of a step of a method according to a third embodiment of the invention. Detailed description of the invention

[0020] Figure 1 schematically illustrates a system 1 for managing a fleet of unmanned vehicles 5 according to the invention. It is a computer system which comprises a supervisor 2 connected to a user interface 3 and to a mission manager 4 which controls the movements of the vehicles in the fleet of unmanned vehicles 5, for example flying and / or rolling drones. The supervisor 2, the user interface 3 and the mission manager 4 are computer devices (e.g. computer, server, supercomputer, etc.) and they communicate (i.e. exchange data) by means of conventional communication networks and protocols, for example the Internet. Thus, the vehicles in the fleet 5 communicate with the supervisor 2 and with the mission manager 4, possibly also with the user interface 3.The role of supervisor 2 is to determine allocations of the machines of the fleet of machines 5 for the accomplishment of a set of missions specified by a user by means of the user interface 3. Another role of supervisor 2 is to maintain in real time a. inventory of the machines that are part of fleet 5. The mission manager 4 ensures, for its part, the control of the movements of the machines of fleet 5. As will be seen in detail below, this architecture is advantageous because the function of determining allocations of the machines of fleet 5 and the function of piloting the machines are carried out by two separate entities, namely the supervisor 3 and the mission manager 4. Indeed, the need for computing resources to assume one or the other of these functions is significant and, by segmenting the performance of these functions in this way, it is possible to minimize the risk that one of the functions slows down or prevents the performance of the other.

[0021] According to the invention, all the elements described above combine to enable the implementation of a method for managing a fleet of unmanned vehicles, as described below in connection with figures 2-4.

[0022] Figure 2 illustrates by means of a flowchart the steps of a method according to a first embodiment of the invention.

[0023] According to a first step 201, the supervisor 2 obtains at least data characterizing a first mission specified by means of the user interface 3. In other words, the implementation of the method according to the invention is initiated as soon as the user specifies by means of the user interface 3 a first mission which must be accomplished by means of the fleet of machines 5.

[0024] Such a specification provides at least one mission type parameter, which is chosen from several pre-established mission types, and, possibly, a mission priority parameter. For example, in the context of carrying out an inventory within a logistics environment, a first pre-established mission type may consist of distributing equipment within the environment, a second pre-established mission type may consist of carrying out an inventory of elements stored in the environment and a third pre-established mission type may consist of carrying out an in-depth inventory of certain locations in the environment. In the military context, a first type of pre-established mission may consist of carrying out reconnaissance of a geographical area, a second type of mission may consist of escorting a flying unit, a third type of mission may consist of carrying out a doubt removal and a fourth type of mission may consist of monitoring a threat.

[0025] Depending on the use case, the priority parameter is a numerical value, which is specified by the user by means of the user interface 3. For other use cases, however, it is the supervisor 2 who will determine during the third step 203 of the method a value of the priority parameter of the first mission according to its type.

[0026] According to an advantageous alternative, the supervisor 2 also obtains during this first step data characterizing an attribute of a machine. In other words, the supervisor 2 obtains parameters which establish, for example, a type of machine (i.e. rolling, flying, aquatic), a speed of movement of the machine or its autonomy, and this, for one or more of the machines of the fleet 5, preferably all. These data are generated according to specifications made by the user prior to the implementation of the method according to the invention during which he defines the attributes of the machines of the fleet 5 by means of the user interface 3. Alternatively, they are generated according to data transmitted by the machines when a connection between them and the supervisor 2 is established prior to the implementation of the method.

[0027] According to another advantageous variant, the supervisor 2 also obtains during this first step data characterizing a time horizon parameter, i.e. a reference duration during which the supervisor 2 will then seek to establish one or more allocations of the machines of the fleet 5 which optimize a certain number of metrics as described below. low. Such a parameter is pre-set or specified by the user by means of the user interface 3.

[0028] Thus, at the end of this first step, the supervisor 2 holds data which have been specified by the user or which he has determined and which provide information on the type of a first mission to be accomplished with the fleet of machines 5 and, possibly, a priority parameter of the mission, attributes of the machines of the fleet 5 and a time horizon applicable to the mission.

[0029] According to a second step 202, the supervisor 2 determines, based at least on the data obtained during the first step, data characterizing a first set of possible allocations of the fleet to accomplish the first mission.

[0030] In other words, supervisor 2 determines at this stage several scenarios for using the vehicles of fleet 5 that allow the first mission to be accomplished depending on the type of mission and the time horizon. Possibly, it determines this set of possible allocations by also taking into account the attributes of the vehicles as well as any failures of these, these being reported to it by the vehicles themselves or determined when supervisor 2 detects a breakdown in communication with a vehicle. The set of possible allocations thus determined establishes in time actions that can be carried out by the vehicles of fleet 5, thus involving movements of one or more vehicles.In terms of implementation, supervisor 2 determines the set of possible allocations in the form of a solution tree, where each branch of the tree corresponds to a possible allocation and each node of the tree corresponds to an intermediate step of the allocation at a given time. In other words, an allocation establishes a succession of steps that each define one or more actions that are carried out by one or more vehicles in fleet 5. Possibly, the tree of possible allocations of the vehicles of. Fleet 5 extends to the time horizon obtained in the previous step of the process.

[0031] Thus, at the end of this second stage, the supervisor determined different ways of allocating the vehicles of fleet 5 to accomplish the first mission.

[0032] According to a third step 203, the supervisor 2 determines, for several allocations of the first set of possible allocations of the fleet 5 which were determined during the previous step, at least data characterizing a first value of quality of completion of the first mission and data characterizing a first value of the risk of not being able to accomplish one or more additional missions. Indeed, the need to be able to produce a solution in as short a time as possible may require at this stage that the supervisor 2 is content to examine only certain allocations of the set of possible allocations which were determined during the previous step.

[0033] Thus, the supervisor determines for certain possible allocations determined during the previous step certain specific metrics. The first metric thus determined with regard to a possible allocation is that of the quality of completion of the first mission. This is determined, for example, as a function of the time horizon, a value of duration of completion of the first mission considered, a value of quality of perception by means of detection devices on board the machines, a value of a ratio between the sum of the surfaces covered by the machines and the surface of a geographical zone (specified by means of the user interface 3 when specifying the first mission) and / or a value of the autonomy of a machine with regard to the geographical zone.

[0034] Concerning the second metric which is determined at this stage by the supervisor 2, it quantifies the risk of not being able to accomplish one or more other missions with regard to a possible allocation. It is determined, for example, according to a probability value which depends on a number of vehicles necessary to accomplish one or more additional missions. Thanks to this second metric, the supervisor 2 advantageously takes into account not only the mission to be accomplished but also the capacity to manage other missions in parallel. This aspect proves to be particularly advantageous for certain applications where the capacity to accomplish new missions can prove crucial, in particular in a military context. In certain use cases however, this parameter is secondary and the supervisor 2 can in this case determine at this stage that the value of the risk of not being able to accomplish at least one additional mission is zero.

[0035] Alternatively, it is during this third step that the supervisor 2 possibly determines a third specific metric by determining data characterizing a value of a priority parameter of the first mission. Indeed, in a use case where the value of the priority parameter of the first mission is not specified by the user by means of the user interface 3 and obtained during the first step of the method, it is the supervisor 2 which determines at this stage the value of a priority parameter of the first mission according to its type.

[0036] According to a fourth step 204, the supervisor 2 determines, based on the data determined during the third step, at least one first particular allocation of the fleet to accomplish the first mission. In other words, the supervisor 2 determines at this stage one or more particular allocations of the vehicles of the fleet 5 from among those for which the metrics were determined during the previous step. Preferably, these particular allocations are those which, over the time horizon, maximize the quality of accomplishment of the first mission and which minimize the risk of not being able to accomplish at least one additional mission over the time horizon. Several specific allocations of fleet 5 are thus determined, for example based on threshold values ​​which are either specified by means of user interface 3 or calculated by supervisor 2 based at least on the type of mission, against which the quality and risk metrics are examined. Thus, at the end of this fourth step, the supervisor has determined several specific allocations of fleet 5 which are the most efficient with regard to the quality and risk metrics.

[0037] According to a fifth step 205, the supervisor 2 transmits data characterizing a first selected allocation of the fleet to accomplish the first mission to the mission manager 4. In other words, the supervisor 2 transmits at this stage to the mission manager 4 a single allocation of the fleet 5 that the latter will take into account to manage the movements of the machines. In a first case, this step is carried out autonomously by the supervisor 2, the latter selecting the particular allocation of the fleet 5 for which the compromise between the quality of accomplishment of the mission and the risk of not being able to accomplish an additional mission is optimal. Alternatively, for certain use cases where it is desired that the user be responsible for the selection of a particular allocation, this step is carried out according to an entry made by the user by means of the user interface 3.In other words, in this case it is the user who selects one of the specific allocations previously determined and who validates the transmission of this selected allocation to the mission manager 4.

[0038] According to a sixth step 206, the mission manager 4 controls the movements of the machines of the fleet 5 according to the data characterizing a first selected allocation which were transmitted to it during the previous step. Thus, at the end of this sixth step, the movements of the machines of the fleet 5 are carried out in accordance with the allocation selected following the implementation of the previous step of the process. Advantageously, the movements of the fleet 5 machines are therefore carried out in a way that optimizes the compromise between the quality of accomplishment of the first mission and the risk of not being able to accomplish an additional mission.

[0039] Figure 3 illustrates by means of a flowchart additional steps of a method according to a second embodiment of the invention which advantageously allows the real-time reallocation of the vehicles of the fleet 5 when one or more new missions to be accomplished are specified.

[0040] For this, according to a seventh step 207, the supervisor 2 obtains at least data characterizing a second mission specified by means of the user interface 3 or as a function of a detection carried out by a machine of the fleet 5. Indeed, a reallocation of the machines of the fleet 5, which can potentially involve one or more of the machines allocated to the first mission, proves necessary in the case where the user specifies another mission by means of the user interface 3. In another case, a reallocation of the machines of the fleet 5 is induced by one of the machines when the latter informs the management system 1 (i.e. the supervisor 2 and / or the mission manager 4) of the benefit of accomplishing an additional mission as a function of a detection that it makes during the accomplishment of a mission.For example, a vehicle from fleet 5 detected a threat when it was allocated to carry out a surveillance mission of an area and, consequently, it specifies and transmits to mission manager 4 a new mission which consists of carrying out a doubt removal in connection with the detected threat. Mission manager 4 then informs supervisor 2 of the interest in carrying out a new mission. And as in the case of the first mission, such a specification of a second mission provides at least a mission type parameter and, possibly, a mission priority parameter.

[0041] According to an eighth step 208, the supervisor 2 determines based on at least the data obtained during the first step and the seventh step, data characterizing a second set of possible allocations of fleet 5 to accomplish the first mission and the second mission. In other words, supervisor 2 proceeds as before but taking into account at this stage all the missions to be accomplished. It thus determines several scenarios for using the machines of fleet 5 which make it possible to accomplish the first mission and the second mission according to the types of missions and the time horizon. Possibly, it determines the second set of possible allocations by also taking into account the attributes of the machines as well as any failures thereof, and possibly the state from the strategic point of view of the machines at a given time. And as before, supervisor 2 determines the second set of possible allocations in the form of a solution tree, which possibly extends to the time horizon.

[0042] According to a ninth step 209, the supervisor 2 determines, for several allocations of the second set of possible allocations of the fleet determined during the previous step, at least data characterizing a second value of quality of accomplishment of the first mission, data characterizing a value of quality of accomplishment of the second mission and data characterizing a second value of the risk of not being able to accomplish one or more additional missions. In other words, new metrics of quality of accomplishment are determined for each of the missions, the first and the second, as well as a new value of the risk of not being able to accomplish an additional mission.

[0043] As previously, the second quality value of completion of the first mission and the quality value of completion of the second mission are determined, for example, as a function of the time horizon, a value of duration of completion of a mission considered, a value of quality of perception by means of detection devices on board the machines, a value of a ratio between the sum of the surfaces covered by the machines and the surface of a geographical zone specified by means of the user interface and / or of a value of the autonomy of a machine with respect to the geographical area. Similarly, the second value of the risk of not being able to accomplish one or more additional missions is determined, for example, based on a probability value which depends on a number of machines necessary to accomplish one or more additional missions.

[0044] According to a variant, it is during this ninth step that the supervisor 2 determines a third metric by determining data characterizing a value of a priority parameter of the second mission in the case where this is not specified by the user by means of the user interface 3.

[0045] According to a tenth step 210, the supervisor 2 determines, based on the data determined during the previous step, in other words the metrics, at least one second particular allocation of the fleet 5 to accomplish the first and second missions. And as in the fourth step, these particular allocations are those which, over the time horizon, optimize the compromise between the quality of completion of the first mission, the quality of completion of the second mission and the risk of not being able to accomplish at least one additional mission over the time horizon. As previously, several particular allocations of the fleet 5 are thus determined, for example based on threshold values ​​against which the quality and risk metrics are examined.

[0046] According to an eleventh step 211, the supervisor 2 transmits data characterizing a second selected allocation of the fleet 5 to accomplish the first and second missions to the mission manager 4. As in the fifth step, this step can be carried out autonomously by the supervisor 2, the latter selecting a particular allocation of the fleet 5 for which the compromise between the quality of accomplishment of the first mission, the quality of accomplishment of the second mission and the risk not being able to perform any additional missions is optimal. Alternatively, for use cases where the user is required to be responsible for selecting a particular allocation, this step is performed based on user input using the user interface 3.

[0047] According to a twelfth step 212, the mission manager 4 controls the movements of the vehicles of the fleet 5 according to the data characterizing a second selected allocation of the fleet to accomplish the first and the second mission. Advantageously, the movements of the vehicles of the fleet 5 are therefore carried out in a manner which optimizes the compromise between the quality of accomplishment of the first mission, the quality of accomplishment of the second mission and the risk of not being able to accomplish an additional mission.

[0048] Figure 4 illustrates by means of a flowchart an additional step of a method according to a third embodiment of the invention, which advantageously makes it possible to ensure the security of the system 1 according to the invention.

[0049] To do this, according to a thirteenth step 213, the supervisor 2 checks its connectivity with the mission manager 4 and with the user interface 3. If it establishes that the connectivity is broken with the user interface 3 and / or the mission manager 4, which means that the management of the fleet vehicles 5 is not operational in accordance with the implementation of the steps of the method according to an embodiment of the invention described above, it terminates the implementation of the method. This ensures the securing of the implementation of the method which requires a constant connection between the user interface 3 and the supervisor 2 and between the supervisor 2 and the mission manager 4.

[0050] Therefore, by means of the method and system according to the invention described above, a solution is provided to enable a user to manage remotely a fleet of unmanned vehicles, in particular according to missions to be accomplished. The invention also allows the management of a fleet of vehicles which can adapt in real time the allocation of vehicles in the fleet for the accomplishment of one or more missions, in particular according to possible failures of the vehicles or new specified missions. It also allows the management of a fleet of vehicles which are not identical in terms of their characteristics and security means to ensure at all times that the management of a fleet of vehicles is operational. Thus, the invention allows the remote management of a fleet of unmanned vehicles in a significantly more advanced manner than known systems.

Claims

CLAIMS:

1. Method for managing a fleet of unmanned vehicles (5) by means of a computer system (1) comprising a supervisor (2) connected to a user interface (3) and to a mission manager (4) which controls the movements of the vehicles, characterized in that said method comprises the following steps: • a first step of obtaining by the supervisor (2) at least data characterizing a first mission specified by means of the user interface (3); • a second stage of determination by the supervisor (2), based at least on the data obtained during the first stage, of data characterizing a first set of possible allocations of the fleet to accomplish the first mission; • a third step of determination by the supervisor (2), for several allocations of the first set of possible allocations of the fleet, of at least data characterizing a first value of quality of accomplishment of the first mission and data characterizing a first value of the risk of not being able to accomplish one or more additional missions; • a fourth stage of determination by the supervisor (2), based on the data determined during the third stage, of at least a first particular allocation of the fleet to accomplish the first mission; • a fifth step of transmission by the supervisor (2) of data characterizing a first selected allocation of the fleet to accomplish the first mission to the mission manager (4); and • a sixth stage of control by the mission manager (4) of the movements of the machines according to the data characterizing a first allocation selected from the fleet to accomplish the first mission.

2. Method according to claim 1, characterized in that the method comprises the following steps: • a seventh step of obtaining by the supervisor (2) at least data characterizing a second mission specified by means of the user interface (3) or according to a detection carried out by a machine • an eighth stage of determination by the supervisor (2), based at least on the data obtained during the first stage and the seventh stage, of data characterizing a second set of possible allocations of the fleet to accomplish the first and second missions; • a ninth step of determination by the supervisor (2), for several allocations of the second set of possible allocations of the fleet, of at least data characterizing a second value of quality of accomplishment of the first mission, data characterizing a value of quality of accomplishment of the second mission and data characterizing a second value of the risk of not being able to accomplish one or more additional missions; • a tenth stage of determination by the supervisor (2), based on the data determined during the ninth stage, of at least a second particular allocation of the fleet to accomplish the first and second missions; • an eleventh step of transmission by the supervisor (2) of data characterizing a second selected allocation of the fleet to accomplish the first and second missions to the mission manager (4); and • a twelfth stage of control by the mission manager (4) of the movements of the machines according to the data characterizing a second selected allocation of the fleet to accomplish the first and second missions.

3. Method according to claim 2, characterized in that the fifth and eleventh steps are carried out based on an input made by means of the user interface (3).

4. Method according to one of claims 2-3, characterized in that the data characterizing a first mission and the data characterizing a second mission contain data characterizing a mission type parameter and data characterizing a mission priority parameter.

5. Method according to one of claims 2-4, characterized in that the second and eighth steps are carried out as a function of data characterizing an attribute or a failure of a machine.

6. Method according to one of claims 2-5, characterized in that the third, fourth, ninth and / or tenth step are carried out by considering a time horizon parameter pre-established or specified by means of the user interface (3).

7. Method according to one of claims 2-6, characterized in that the third step comprises a step of determining data characterizing a value of a priority parameter of the first mission and / or the ninth step comprises a step of determining data characterizing a value of a priority parameter of the second mission.

8. Method according to one of claims 2-7, characterized in that the data characterizing a first value of quality of completion of the first mission, the data characterizing a second value of quality of completion of the first mission and the data characterizing a value of quality of completion of the second mission are determined as a function of a value of duration of completion of a mission considered, of a value of quality of perception by means of detection devices on board the machines, of a value of a ratio between the sum of the surfaces covered by the machines and the surface area of ​​a geographical area specified by means of the user interface (3) and / or a value of the autonomy of a machine with respect to the geographical area.

9. Method according to one of claims 2-8, characterized in that the data characterizing a first value of the risk of not being able to accomplish one or more additional missions and the data characterizing a second value of the risk of not being able to accomplish one or more additional missions are determined as a function of a probability value which depends on a number of devices necessary to accomplish the additional mission(s).

10. Method according to one of claims 2-9, characterized in that the method comprises a thirteenth step of verification by the supervisor (2) of its connectivity with the mission manager and with the user interface.

11. Computer system (1) for managing a fleet of unmanned vehicles (5), characterized in that said system comprises a supervisor (2) connected to a user interface (3) and to a mission manager (4) which jointly implement a method according to one of the preceding claims.

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