Method and system for managing a fleet of unmanned vehicles

Abstract

The invention relates to a 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 a mission manager (4) that controls the movements of the vehicles. The invention also relates to a computer system (1) implementing such a method. Figure for the abstract: 1

Description

Title of the invention: 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, particularly drones. The invention relates specifically 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 a mission manager that controls the movement of the vehicles. The invention also relates to a computer system implementing such a method. The invention is applicable to unmanned vehicles, such as, for example, rolling or flying drones, particularly those used for inventory management in logistics environments. 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, such as a remote control and a virtual reality headset. However, some applications require the use of a fleet of vehicles, and in this case, it is no longer possible to manage the movements of each vehicle manually and individually. When it comes to managing the movements of a fleet of vehicles rather than a single unmanned vehicle, the management systems that are well-known are those that allow the management of the movements of a fleet of drones used for sound and light shows or pyrotechnics.However, these systems only allow for basic drone movement management, limiting themselves to specifying trajectories that are then used to control the movements of each individual drone. No known system currently offers more sophisticated management of these devices, particularly when considering the different types of missions a fleet of drones might undertake, such as inventory management in logistics environments or military applications. For instance, no known system allows for the automated allocation of drones within a fleet to one or more specific missions. 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, particularly in relation to missions to be accomplished. The invention also aims to enable the management of a fleet of vehicles that can adapt the allocation of vehicles in real time for the completion of one or more missions, particularly in response to potential vehicle failures or newly 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 further aims to provide a system that includes security measures to ensure that the management of a fleet of vehicles is operational at all times. The invention thus seeks 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 a mission manager that controls the movements of the vehicles, the method comprising the steps of: • a first step of obtaining by the supervisor at least the 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 allocations of the fleet to accomplish the first mission; • a third step of determination by the supervisor, for several allocations of the first set of possible fleet allocations, of at least data characterizing a first value of quality of execution 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 one initial specific allocation of the fleet to accomplish the first mission; • a fifth transmission step by the data supervisor characterizing an initial selected allocation of the fleet to accomplish the first mission, addressed to the mission manager; and • a sixth step of control by the mission manager of the movements of the vehicles according to the data characterizing a first allocation selected of the fleet to accomplish the first mission.

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

[0006] According to one variant, the fifth and eleventh steps can be carried out based on input made using 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 pre-established or specified time horizon parameter via the user interface.

[0010] According to yet another variant, the third step may include a data determination step characterizing a value of a priority parameter of the first mission and / or the ninth step may include a determination step of 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 execution of the first mission, the data characterizing a second value of quality of execution of the first mission and the data characterizing a value of quality of execution of the second mission can be determined as a function of a value of duration of execution of a mission considered, a value of quality of perception by means of detection devices on board the vehicles, a value of a ratio between the sum of the areas covered by the vehicles and the area of ​​a geographical zone specified by means of the user interface and / or a value of the autonomy of a vehicle with respect 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 vehicles needed to accomplish the additional mission(s).

[0013] According to another embodiment, the process may include 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 method as described above. Brief description of the figures

[0015] Other features and advantages of the invention will become apparent from an examination of the detailed description below, and the accompanying 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 process according to a first method of implementation publication of the invention;

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

[0019] [Fig.4] is a flowchart of a step of a process 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 comprising a supervisor 2 connected to a user interface 3 and 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 computing devices (e.g., computer, server, supercomputer, etc.) and they communicate (i.e., exchange data) using conventional communication networks and protocols, for example, the Internet. Thus, the vehicles in the fleet 5 communicate with the supervisor 2 and the mission manager 4, and possibly also with the user interface 3. The role of the supervisor 2 is to determine the allocation of vehicles in the fleet 5 for carrying out a set of missions specified by a user via the user interface 3. Another role of the supervisor 2 is to maintain a real-time inventory of the vehicles that are part of the fleet 5.Mission manager 4, for its part, controls the movements of the vehicles in fleet 5. As will be seen in detail below, this architecture is advantageous because the function of determining the allocation of vehicles in fleet 5 and the function of piloting the vehicles are carried out by two separate entities, namely supervisor 3 and mission manager 4. Indeed, the computing resources required to perform either of these functions are significant, and by segmenting the execution of these functions in this way, the risk of one function slowing down or preventing the execution of the other is minimized.

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

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

[0023] According to a first step 201, the supervisor 2 obtains at least some 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 vehicles 5.

[0024] Such a specification provides at a minimum a mission type parameter, which is chosen from several pre-established mission types, and, possibly, a mission priority parameter. For example, in the context of conducting an inventory within a logistics environment, a first pre-established mission type might consist of redistributing equipment within the environment, a second pre-established mission type might consist of taking an inventory of items stored in the environment, and a third pre-established mission type might consist of conducting a thorough inventory of certain locations within the environment. In a military context, a first pre-established mission type might consist of carrying out a reconnaissance In the birth of a geographical area, a second type of mission may consist of escorting a navigating unit, a third type of mission may consist of carrying out a verification and a fourth type of mission may consist of tracking a threat.

[0025] Depending on the use case, the priority parameter is a numeric value, which is specified by the user using the user interface 3. For other use cases, however, it is the supervisor 2 who will determine during the third step 203 of the process 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 vehicle. In other words, the supervisor 2 obtains parameters that establish, for example, a vehicle type (i.e., road, air, water), a vehicle speed, or its range, for one or more of the vehicles in the fleet 5, preferably all of them. This data is generated based on specifications made by the user prior to implementing the method according to the invention, during which the user defines the attributes of the vehicles in the fleet 5 using the user interface 3. Alternatively, it is generated based on data transmitted by the vehicles when a connection between them and the supervisor 2 is established prior to implementing the method.

[0027] According to another advantageous embodiment, the supervisor 2 also obtains during this first step data characterizing a time horizon parameter, i.e., a reference period during which the supervisor 2 will then seek to establish one or more allocations of the fleet's vehicles 5 that optimize a number of metrics as described below. Such a parameter is pre-established or specified by the user via the user interface 3.

[0028] Thus, at the end of this first step, the supervisor 2 holds data which has been specified by the user or which he has determined and which informs the type of a first mission to be accomplished with the fleet of vehicles 5 and, possibly, a priority parameter of the mission, attributes of the vehicles 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 fleet allocations to accomplish the first mission.

[0030] In other words, supervisor 2 determines at this stage several scenarios for using the vehicles in 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 also taking into account the attributes of the vehicles as well as Potential failures of these vehicles are reported to the system either by the vehicles themselves or determined when supervisor 2 detects a communication breakdown with a vehicle. The resulting set of possible allocations establishes actions over time that can be performed by the vehicles in fleet 5, thus involving the movement of one or more vehicles. In terms of implementation, supervisor 2 defines the set of possible allocations as 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 in the allocation at a given time. In other words, an allocation establishes a sequence of steps, each defining one or more actions that are performed by one or more vehicles in fleet 5.Possibly, the allocation tree for the fleet 5 vehicles extends to the time horizon obtained during the previous step of the process.

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

[0032] According to a third step 203, supervisor 2 determines, for several allocations from the first set of possible fleet allocations 5 that were determined during the previous step, at least data characterizing a first quality value for the completion of the first mission and data characterizing a first risk value for the inability to complete one or more additional missions. Indeed, the need to be able to produce a solution in as short a time frame as possible may require supervisor 2 at this stage to examine only certain allocations from the set of possible allocations that were determined during the previous step.

[0033] Thus, the supervisor determines specific metrics for certain possible allocations identified during the previous step. The first metric thus determined for a possible allocation is the quality of execution of the first mission. This is determined, for example, based on the time horizon, a value for the duration of the first mission, a value for the quality of perception using detection devices onboard the vehicles, a value for the ratio between the sum of the areas covered by the vehicles and the area of ​​a geographical zone (specified using user interface 3 when specifying the first mission), and / or a value for the autonomy of a vehicle with respect to the geographical zone.

[0034] Regarding the second metric, which is determined at this stage by supervisor 2, it quantifies the risk of not being able to complete one or more additional missions with respect to a possible allocation. It is determined, for example, based on a probability value that depends on the number of aircraft needed to complete one or more additional missions. Thanks to this second metric, the supervisor 2 can determine the risk of not being able to complete one or more additional missions. Supervisor 2 advantageously considers not only the mission to be accomplished but also the capacity to manage other missions in parallel. This aspect proves particularly beneficial for certain applications where the ability to accomplish new missions can be crucial, especially in a military context. In some use cases, however, this parameter is secondary, and Supervisor 2 can then determine at this stage that the risk of being unable 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 via the user interface 3 and obtained during the first step of the process, it is the supervisor 2 that determines at this stage the value of a priority parameter of the first mission based on its type.

[0036] According to a fourth step 204, supervisor 2 determines, based on the data determined during the third step, at least one initial specific allocation of the fleet to accomplish the first mission. In other words, supervisor 2 determines at this stage one or more specific allocations of the vehicles in the fleet 5 from among those for which the metrics were determined during the previous step. Preferably, these specific allocations are those which, over the time horizon, maximize the quality of the first mission and 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 ​​that are either specified using the user interface 3 or calculated by the supervisor 2 based at a minimum 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 that 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 the mission manager 4 to accomplish the first mission. In other words, at this stage, the supervisor 2 transmits to the mission manager 4 a single allocation of the fleet 5, which the latter will take into account to manage the movements of the vehicles. In a first case, this step is carried out autonomously by the supervisor 2, which selects the particular allocation of the fleet 5 for which the compromise between the quality of mission completion and the risk of not being able to accomplish a further mission is optimal. Alternatively, for certain use cases where it is desired that the user is responsible for selecting a particular allocation, this step is carried out based on an input made by the user using the user interface 3. In other words, in this case it is the user who selects one of the previously determined particular allocations 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 vehicles in fleet 5 based on data characterizing a first selected allocation, which was transmitted to it during the previous step. Thus, at the end of this sixth step, the movements of the vehicles in 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 vehicles in fleet 5 are therefore carried out in a way that optimizes the trade-off between the quality of completion of the first mission and the risk of being unable to complete a subsequent mission.

[0039] Figure 3 illustrates by means of a flowchart additional steps of a process 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 purpose, 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 based on a detection made by a vehicle from the fleet 5. Indeed, a reallocation of vehicles from the fleet 5, which may potentially involve one or more of the vehicles allocated to the first mission, is necessary in the case where the user specifies another mission by means of the user interface 3. In another case, a reallocation of vehicles from the fleet 5 is induced by one of the vehicles when it informs the management system 1 (i.e. the supervisor 2 and / or the mission manager 4) of the interest in carrying out an additional mission based on a detection it makes during the execution of a mission.For example, a vehicle from fleet 5 detected a threat while assigned to a surveillance mission in an area and, consequently, it specifies and transmits to mission manager 4 a new mission to investigate the detected threat. Mission manager 4 then informs supervisor 2 of the need to perform a new mission. And as with 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 at least on the data obtained during the first and seventh steps, the data characterizing a second set of possible allocations for Fleet 5 to accomplish the first and second missions. In other words, Supervisor 2 proceeds as before, but at this stage, taking into account all the missions to be accomplished. It thus determines several scenarios for using the vehicles in Fleet 5 that allow the first and second missions to be accomplished, depending on the mission types and the time horizon. It may also determine the second set of possible allocations by considering the vehicle attributes, potential failures, and possibly the strategic status of the vehicles at a given time. And as before, Supervisor 2 determines the second set of possible allocations in the form of a solution tree, which may extend to the time horizon.

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

[0043] As before, the second quality value for the completion of the first mission and the quality value for the completion of the second mission are determined, for example, based on the time horizon, a duration value for the completion of a given mission, a quality value for perception using detection devices onboard the vehicles, a value representing the ratio between the sum of the areas covered by the vehicles and the area of ​​a geographical zone specified by the user interface, and / or a value for the autonomy of a vehicle in relation to the geographical zone. Similarly, the second value for the risk of not being able to complete one or more additional missions is determined, for example, based on a probability value that depends on the number of vehicles required to complete one or more additional missions.

[0044] According to one 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, i.e., the metrics, at least one second specific allocation of the fleet 5 to accomplish the first and the second mission. And as in the fourth step, these specific allocations are those which, over the time horizon, optimize the trade-off between the quality of execution of the first mission, the quality of execution of the second mission, and the risk of not being able to complete at least one additional mission over the time horizon. As before, several specific allocations of 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 from the fleet 5 to the mission manager 4, specifying the allocation for completing the first and second missions. As in the fifth step, this step can be performed autonomously by the supervisor 2, who selects a particular allocation from the fleet 5 for which the trade-off 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 complete an additional mission is optimal. Alternatively, for use cases where the user is responsible for selecting a particular allocation, this step is performed based on input made by the user via the user interface 3.

[0047] According to a twelfth step 212, the mission manager 4 controls the movements of the vehicles in fleet 5 based on data characterizing a second allocation selected from the fleet to accomplish the first and second missions. Advantageously, the movements of the vehicles in fleet 5 are thus carried out in a way that optimizes the trade-off between the quality of completion of the first mission, the quality of completion of the second mission, and the risk of being unable to complete an additional mission.

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

[0049] To this end, 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 determines that connectivity is broken with the user interface 3 and / or the mission manager 4, meaning that the fleet vehicle management 5 is not operational in accordance with the implementation of the steps of the process according to an embodiment of the invention described above, it terminates the implementation of the process. This ensures the security of the process implementation, 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, thanks to the method and system according to the invention described above, A solution is provided to enable a user to remotely manage a fleet of unmanned aerial vehicles (UAVs), particularly in relation to missions to be completed. The invention also allows for the management of a fleet of vehicles that can adapt the allocation of vehicles in real time to accomplish one or more missions, notably in response to potential vehicle failures or newly specified missions. Furthermore, it allows for the management of a fleet of vehicles that are not identical in terms of their characteristics and security measures, ensuring that fleet management remains operational at all times. Thus, the invention enables the remote management of a fleet of unmanned aerial vehicles in a significantly more advanced manner than existing systems.

Claims

Demands

1. A 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 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 some data characterizing a first mission specified by means of the user interface (3); • a second step of determining by the supervisor (2), 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;• a third step of determination by the supervisor (2), for several allocations from the first set of possible fleet allocations, of at least data characterizing a first value of the quality of completion of the first mission and data characterizing a first value of the risk of not being able to complete one or more additional missions; • a fourth step of determination by the supervisor (2), based on the data determined during the third step, of at least a first particular allocation of the fleet to complete the first mission; • a fifth step of transmission by the supervisor (2) of data characterizing a first selected allocation of the fleet to complete the first mission to the mission manager (4);and • a sixth step of control by the mission manager (4) of the movements of the vehicles according to the data characterizing a first selected allocation of the fleet to accomplish the first mission.;

2. The method according to claim 1, characterized in that the method comprises the following steps:

3.

4. • a seventh step of obtaining by the supervisor (2) at least the data characterizing a second mission specified by means of the user interface (3) or according to a detection carried out by a device; • an eighth step of determination by the supervisor (2), based at least on the data obtained during the first step and the seventh step, of data characterizing a second set of possible allocations of the fleet to accomplish the first and second mission; • a ninth determination step by the supervisor (2), for several allocations of the second set of possible fleet allocations, of at least data characterizing a second quality value of completion of the first mission, data characterizing a quality value of completion of the second mission and data characterizing a second value of the risk of not being able to complete one or more additional missions; • a tenth determination step by the supervisor (2), based on the data determined during the ninth step, of at least a second specific 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 step of control by the mission manager (4) of the movements of the vehicles according to the data characterizing a second selected allocation of the fleet to accomplish the first and second mission. Method according to claim 2, characterized in that the fifth and eleventh steps are carried out according to an input made by means of the user interface (3). A method according to any 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 parameter mission priority.

5. A method according to any one of claims 2-4, characterized in that the second and eighth steps are carried out based on data characterizing an attribute or failure of a machine.

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

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

8. A method according to any one of claims 2-7, characterized in that the data characterizing a first quality value of the first mission, the data characterizing a second quality value of the first mission and the data characterizing a quality value of the second mission are determined as a function of a value of the duration of completion of a given mission, a value of the quality of perception by means of detection devices on board the vehicles, a value of a ratio between the sum of the areas covered by the vehicles and the area of ​​a geographical zone specified by means of the user interface (3) and / or a value of the autonomy of a vehicle with respect to the geographical zone.

9. A method according to any 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 vehicles needed to accomplish the additional mission(s).

10. A method according to any one of claims 2-9, characterized in that the method includes 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 a mission manager (4) which jointly implement a method according to one of the preceding claims.

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