• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
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    • 专利摘要:
    This swarm (101) consists of a plurality of drones (111-115), the drones being flying drones, the drones forming between them a communication network. It is characterized in that the swarm implements, autonomously, an obstacle avoidance functionality (20) based on collaborative observation of the environment of the swarm by each of the drones and the sharing of information obstacle detection between the drones.
    公开号:FR3071093A1
    申请号:FR1700905
    申请日:2017-09-08
    公开日:2019-03-15
    发明作者:Gilles Guerrini；Patrick Garrec；Ema FALOMIR
    申请人:Thales SA；
    IPC主号:
    专利说明:

    ESSAIM CONSISTS OF A PLURALITY OF LIGHT FLYING DRONES
    The invention relates to that of swarms of flying drones. It relates more particularly to the obstacle detection and avoidance functionalities for such swarms.
    One of the main interests of a drone swarm is that it can be viewed by the operator who controls it remotely as a single entity.
    For this to be possible, certain functionalities must be managed by the swarm itself, without operator intervention.
    Among these functions managed independently by the swarm, there is in particular the functionality of determining the individual trajectories of each of the drones.
    This functionality must make it possible to carry out the mission assigned to the swarm, for example to go to a predefined destination point, taking into account the relief of the terrain overflown; the weather ; the presence of fixed or mobile obstacles to avoid them; the presence of other drones in the swarm to avoid internal collisions in the swarm; and possibly the malfunction of one or more swarm drones.
    The functionality for determining individual trajectories is notably based on an obstacle detection functionality in order to avoid them.
    Currently, obstacle detection is carried out by a main drone, known as a "detector" drone, which carries a system of sensors allowing a complete observation of the swarm environment. By complete, we mean the ability of the sensor system to observe at least an area of +/- 110 ° in azimuth and +/- 10 ° in elevation, over a depth of several hundred meters. This corresponds to what is asked of the pilot of a fixed-wing aircraft in terms of field of vision.
    For example, the sensor system includes a radar for long distance obstacle detection and an optical camera for the identification of obstacles detected by the radar.
    This effective solution, however, involves embarking on the platform constituted by the drone an elaborate and consequently expensive system of sensors.
    Since such a sensor system also has significant weight, it is necessary to size the "detector" drone so that it can carry such a load. It is therefore not a mini-drone, or light drone, that is to say a small drone of the four-engine type, such as those which can be found commercially for the General public.
    It is in any case different from other swarm drones.
    If this "detector" drone is destroyed or breaks down during the mission, the swarm is no longer able to detect and therefore avoid obstacles. The accomplishment of the mission is then totally compromised.
    Furthermore, it is not possible to provide each of the drones in the swarm with such a system of sensors, since each of the drones would have to be sized so that it can carry such a load. Consequently, this solution is only possible for powerful drones, which would therefore not be light drones. This solution would have a significant cost in terms of platform and sensor system.
    Other solutions are envisaged, such as the detection of obstacles by the ground, then the communication of the detection information from the ground detection station to the drones.
    However, this solution involves communications between the ground and the swarm during the completion of the mission. Such communications lack discretion.
    In addition, observing the environment of the swarm from the ground is not good for grazing angles, so that the detection of obstacles on the ground (bridge, pylons, etc.) is of poor quality.
    Finally, if obstacle detection is carried out in this way, we are no longer in the context of a function managed independently by the swarm.
    Another solution is to make a map of the region where the mission is taking place, mentioning in particular the obstacles to avoid. This map is stored in the drones memory and is taken into account when carrying out the mission. Again, detection is not carried out autonomously by the swarm.
    But above all, such a solution does not allow the detection of mobile obstacles in the mapped region.
    Finally, the swarm cannot venture outside the region corresponding to the stored card.
    The invention therefore aims to provide an alternative to the previous solutions, in particular a solution which can be implemented independently by the swarm.
    For this, the invention relates to a swarm consisting of a plurality of drones, the drones being flying drones, the drones forming between them a communication network, characterized in that the swarm implements, autonomously, a obstacle avoidance functionality based on a collaborative observation of the swarm environment by each of the drones and the sharing of obstacle detection information between the drones.
    According to particular embodiments, the swarm includes one or more of the following characteristics, taken in isolation or in any technically possible combination:
    each drone embarks: a system of sensors allowing the observation of the swarm environment inside a partial observation envelope and the generation of obstacle detection information in the event of the presence of a obstacle inside said partial observation envelope; a radiocommunication means for establishing at least one communication link with another swarm drone for the exchange of obstacle detection information; and a calculation unit suitable for calculating an individual trajectory of said drone from the obstacle detection information generated by said drone or received from another drone of the swarm.
    the calculation unit of each drone is suitable for determining a relative position and / or a relative speed of at least one drone close to said drone, the calculation unit of said drone calculating the individual trajectory of said drone taking into account, moreover , said relative position and / or said relative speed.
    the calculation unit of each drone calculates the individual trajectory of said drone so that the swarm adopts an optimized configuration.
    the configuration is optimized by maximizing an area of the environment observed by the swarm, the observed area corresponding to the meeting of the partial observation envelopes of each drone of the swarm.
    the swarm moving in a main direction, the drones are oriented so that the observed area is preferably in front of the drone swarm.
    the configuration is optimized so that a topology of the communication network formed by the drones of the swarm is connected, preferably bi-connected.
    the swarm is able to deviate from its optimized configuration by deformation to avoid an obstacle, then to resume the initial optimized configuration after having overcome the obstacle.
    the configuration is optimized so that a distance between two nearby drones is constrained around a reference distance.
    the drones are identical to each other, the sensor systems on board by each of the drones being identical.
    the drones are different, the sensor systems on board each of the drones being identical or different, the swarm being heterogeneous.
    each drone is a light drone, with a total wingspan, less than one meter.
    the calculation unit of a drone stores a matrix covering the swarm environment, the matrix being subdivided into cells, each cell in which an obstacle has been detected being associated with a flag, an update of the matrix being performed from obstacle detection information generated by said drone or received from another drone of the swarm.
    the dimensions of the matrix cells depend on the partial observation envelopes of the swarm drone sensor systems.
    The invention also relates to a method for detecting and avoiding an obstacle implemented in a swarm conforming to the preceding swarm, characterized in that it comprises the steps consisting in: adoption by the swarm of '' an optimized configuration; observation of an area of the environment corresponding to the meeting of the partial observation envelopes of each drone of the swarm; sharing obstacle detection information generated by a drone with the other swarm drones using the communication network established between the swarm drones; and calculation by each drone of its individual trajectory taking into account the obstacle detection information that it has generated and / or that it has received from other drones.
    According to particular embodiments, the method comprises one or more of the following characteristics, taken in isolation or according to all technically possible combinations:
    The invention and its advantages will be better understood on reading the detailed description which follows of a particular embodiment, given solely by way of nonlimiting example, this description being made with reference to the appended drawings in which:
    - Figure 1 is a schematic representation of a swarm of seven drones adopting an optimal configuration for obstacle detection and their avoidance;
    - Figures 2 to 5 show a swarm of five drones in different successive configurations during the avoidance of a detected obstacle; and,
    - Figure 6 is a schematic representation of a mapping of the environment advantageously used by each of the drones of the swarm.
    GENERAL PRINCIPLE
    According to the invention, each swarm of the swarm carries a system of sensors of reduced weight and inexpensive, but which allows the observation only of a limited fraction of the environment of the swarm. The geometry of this partial observation envelope depends on the angular coverage of the chosen on-board sensor (s).
    While each drone can only observe the environment within a reduced observation envelope, the drones share the obstacle detection information they produce by exchanging it over the network. of communication that they establish among themselves.
    Each drone can then draw up a representation of the environment indicating the obstacles to be avoided. The obstacle detection functionality is therefore distributed between the various drones.
    On the basis of this representation, each drone determines its individual trajectory in real time so as to avoid collisions with the obstacles detected.
    The calculation of the individual trajectory takes into account other information, such as the relative position and / or the relative speed of the other drones of the swarm so as to avoid collisions with the other drones of the swarm.
    The swarm adopts a configuration allowing to optimize the area covered by the individual observation envelopes, while optimizing the communication network between drone (each drone representing a node of the network and each communication link between two drones constituting a link between two network nodes).
    In particular, the observation area is optimized by properly orienting the observation direction of the drone sensor systems relative to a direction of movement of the entire swarm.
    The network is optimized by securing the number of communication links established between the swarm drones.
    While the swarm has adopted a particular configuration, the avoidance of an obstacle results in a deformation of the swarm, which returns to its initial configuration once the obstacle has been overcome.
    This solution makes it possible to miniaturize the system of sensors on board by each drone, to reduce its weight and consequently to allow the use of small platforms.
    This solution also allows a greater reactivity of the swarm since the small drones have an extremely reduced inertia and consequently a reactivity lower than the second.
    In this scheme, the loss of a swarm drone results in real-time reconfiguration of the swarm made up of the remaining drones. The obstacle detection and avoidance function can still be achieved, and the mission that the swarm must fulfill can still be achieved.
    STRUCTURE
    A drone swarm consists of a plurality of N drones.
    In Figure 1, the swarm 1 consists of seven drones 11 to 17, while in Figures 2 to 6, the swarm 101 consists of five drones 111 to 115.
    As illustrated in FIG. 2, a drone, such as drone 11, is a flying platform, for example a multirotor, such as those which can be found in commerce for the general public,
    It is small. For example, it has a total wingspan of less than one meter.
    It comprises for example four rotors 21 rotated by motors 22, supplied by suitable supply means 23 and controlled by suitable actuation means 24.
    Such a drone can for example fly at a maximum speed of 50 km / h.
    It has reduced inertia, giving it great maneuverability.
    A drone 11 has a sensor system 30. It is one or more sensors allowing observation of the environment on a partial observation envelope. The drone observation envelopes 11 to 17 are referenced 41 to 47.
    The observation envelope, for example, has an opening of 90 ° in azimuth and + / 10 ° in elevation and a limited range, but sized according in particular to the maximum speed of the drone used.
    The scope is for example dimensioned in the following manner. Since drones have a maximum speed of around 50 km / h, the detection distance must make it possible to avoid a frontal collision between two swarms moving towards each other, each at 14 m / s, i.e. 28 m / s on approach. As the inertia is negligible, detection at a distance of 50 meters is sufficient provided that the communication times between the drones of a swarm are minimal. It will therefore be necessary to adapt the topology of the communication network that constitutes the swarm according to this constraint.
    A sensor system 30 consisting of a low-cost optical camera responds to this dimensioning of the detection range.
    Preferably, the camera also operates in the infrared range, so as to be able to confirm the detections in the optical range from a thermal signature of the detected obstacle.
    Advantageously, the sensor system 30 incorporates a sound sensor (or sonar) making it possible to redundant the camera at a lower cost and with less bulk.
    Alternatively, other types of sensors could be used such as a radar sensor, a lidar sensor, or any combination of the types of sensors just mentioned.
    In the embodiment envisaged, the various drones 11 to 17 of the swarm 1 are identical, when they are considered independently of the system of sensors that they carry. If the drone sensor systems are identical to each other, the drones are said to be identical. If the drone sensor systems are different, the drones are said to be similar.
    As a variant, the different drones of the swarm are different, when we consider them independently of the sensor system they carry. We will then talk about different drones whether they carry identical or different sensor systems. The swarm is then said to be heterogeneous.
    The drone 11 comprises a radiocommunication module 40 allowing the establishment of communication links with other drones of the swarm. The drones with which a drone has established, at the current time, a communication link are said to be "neighboring" drones of the drone considered. In FIG. 1, the links established are represented by dotted lines. For example, drone 12 has neighboring drones, drones 11, 13, 14 and 16.
    Advantageously, the communication between two drones is done in wide or ultra wide band (“Ultra Wide Band” in English), which has the advantage of allowing an easy determination of the distance between the two drones in communication, as is known from the skilled person.
    A drone can for example establish a maximum of three links. In fact, beyond this maximum number of links, the bandwidth may be insufficient.
    The drone 11 also has a calculation unit 50 comprising a processor and a memory. The processor is capable of executing the instructions of computer programs stored in the memory.
    In particular, the computing unit 50 executes an obstacle detection program 52.
    This program allows, when executed on a drone, for example the drone 11, the acquisition and processing of the signals delivered by the sensor (s) of the sensor system 30 of the drone 11, to generate detection information. obstacle.
    It also allows the exchange of detection information with other drones. The drone 11 thus transmits the detection information which it has produced and receives from its neighbors detection information produced by other drones of the swarm.
    Finally, it allows updating of a matrix stored in the memory of the drone 11, such as the matrix 80 shown in FIG. 7.
    This matrix is a representation of the swarm environment.
    The matrix consists of a plurality of cells surrounding the environment of the swarm.
    FIG. 7 schematically represents such a matrix, subdivision of the space surrounding the swarm into a plurality of cells.
    Two solutions can be envisaged: the matrix relates to the swarm and it is for example determined in a frame of reference associated with a particular, so-called main drone, or at the barycenter of the swarm drones; where the matrix is predefined with respect to the terrain, that is to say fixed with respect to the soil, which is of interest when using a digital terrain model.
    The cells of the matrix are advantageously adapted to the dimensions of the observation envelopes of the drone sensor systems.
    A flag is associated with a cell when an obstacle is detected in said cell. Advantageously, the flag indicates the instant of detection of the obstacle and is only kept for a suitable period of persistence.
    The computing unit 50 also executes a program 54 for determining the instantaneous configuration of the swarm.
    It is preferable that each drone has a knowledge of the general configuration of the swarm at all times. However, to do this, the amount of information to be exchanged on the network so that each of the drones can maintain this knowledge is too large, not always useful and risks penalizing the exchange of obstacle detection information considered to be priority.
    It is therefore envisaged to limit the knowledge that a drone has of the configuration of the swarm to the position of geographically close drones, so as to limit the information to be transmitted over the communication network. By close drones is meant all of the drones located within a volume centered on the drone considered and having an extension in the direction of the speed V of movement of the swarm which depends on the amplitude of this speed. For example, if when stopped, this volume is a sphere of radius R, during the movement of the swarm, this volume deforms into an ovoid of minor axis R in the direction perpendicular to the speed V and of major axis R (1 + V / V0), where V0 is a reference speed, in the direction of speed V. Such a volume is represented by a dashed line in Figure 1 for the drone 12. The drones geometrically close to the drone 12 are drones 11, 14 and 16.
    The determination of the relative position between two drones which are both close and neighboring is carried out for example by measuring the distance between two drones having established a UWB radio link, as indicated above, possibly coupled with a measurement of angle between the two drones using an on-board goniometer system.
    Determining the relative position between two nearby drones that are not neighboring involves determining relative positions relative to an intermediate drone and exchanging these measurements on the network.
    The calculation unit 50 executes a program 56 for calculating the individual trajectory of the drone 11. The calculated trajectory is used by the means 24 for the adapted actuation of the motors and the displacement of the drone, in particular so as to avoid an obstacle or a collision with another drone.
    On a communication link, a drone is finally able to exchange messages with its neighbors containing the following information:
    - an identifier of the drone sending the message;
    - the instantaneous position and the instantaneous speed of the transmitting drone;
    - the identifiers of drones neighboring the transmitting drone;
    - relative position information between the transmitting drone and nearby drones, such as for example the distance between these drones and the angle between these drones; and,
    - obstacle detection information generated by the transmitting drone or received by the transmitting drone from a neighboring drone.
    This obstacle detection information takes, for example, the form of a list indicating the coordinates of the cells of the matrix in which an obstacle has been detected and the associated flag.
    A drone can receive the same detection information from several of its neighbors. These redundancies advantageously allow the implementation of an integrity check.
    OPERATION
    The operation of the swarm will now be described with reference to Figures 3 to 6.
    Each drone 111 to 115 of the swarm 101 moves in a main direction (corresponding to the direction of the speed V of the swarm), towards a common objective, defined in the mission assigned to the swarm and memorized by each of the drones. This objective is constituted for example by a geographical point of destination.
    For its movement, the swarm 101 dynamically adopts a configuration which results from the optimization of a cost function allowing the taking into account of various constraints, in particular a first constraint of optimized observation of the environment and a second constraint d optimization of the communication network topology within the swarm.
    The first constraint forces the swarm to adopt a configuration allowing observation of the environment with optimal coverage. In particular, the various partial observation envelopes of the drone sensor systems are oriented as a function of each other and of the main direction of movement of the swarm to maximize the probability of detection of the mobile or fixed obstacles with which the either of the drones in the swarm may collide.
    Each drone is thus dynamically assigned to an observation task consisting of observing a sector of the environment, in particular certain cells of the matrix when such mapping is used. The observation task depends on the position of the drone considered in the configuration adopted.
    Priority is given to the areas of the environment in front of the swarm, that is to which the swarm is moving.
    Thus, the drone detection envelopes 111 and 112 disposed on the front front of the configuration adopted by the swarm 101 are oriented forward and slightly adjoin or overlap at their edges so as to monitor spatially continues the sector located in front of the swarm.
    Advantageously, the drones 113 and 114 located on a lateral front of the configuration move so that their direction of observation and their direction of movement face an angle suitable for the observation of a sector located on the side of the 'swarm.
    Advantageously, the drone 115 located on a rear front of the configuration moves so that its direction of observation and its direction of movement makes an angle suitable for the observation of a sector located at the rear of the swarm, so as to be able to detect moving obstacles approaching the swarm from the rear.
    The second constraint forces the swarm to adopt a configuration optimizing the network topology. Advantageously, the network topology is related, that is to say that each drone can exchange messages with all the other drones of the swarm either directly (that is to say with a neighboring drone, like the drone 112 with drones 111, 113 and 114) or indirectly via drone (s) playing the role of relay nodes (such as drone 112 with drone 115 via drone 114).
    Advantageously, the network topology is bi-connected, so that if any drone is deleted, the swarm remains connected.
    The second constraint on the network topology also implies that a distance between two drones is maintained around a reference distance DO during the movement of the swarm and the avoidance of obstacles.
    This reference distance DO is for example considered to be the minimum between the maximum range of the means of communication between two drones (for example 300 meters in the case of an ultra wide band UWB system) and twice the range of the sensors. In this way, when an obstacle is detected by a drone, the latter is able to transmit a message adapted to the other drones of the swarm, and the drones have time to modify their trajectories to avoid the detected obstacle as well as any internal collision in the swarm.
    Furthermore, this reference distance D0 makes it possible to anticipate a loss of the communication link between two drones, when the distance between two drones in communication increases beyond the value D0.
    An example of an optimized configuration is shown in FIG. 3 with a swarm 101 consisting of five drones adopting a substantially regular pentagon configuration.
    During the movement of the swarm 101, each drone acquires the signals delivered by its sensor system and processes them so as to detect the presence of an obstacle in its observation envelope and to determine the position of the 'obstacle.
    The position of an obstacle is for example given by the coordinates of the cell of the matrix inside which this obstacle has been detected.
    As soon as a drone detects an obstacle, it shares this detection information with its neighbors, by transmitting a suitable message.
    When receiving a message containing obstacle detection information generated by a neighbor, a receiving drone transmits to its neighbors a message containing this detection information. Thus, the initial detection information is shared among all the drones of the swarm.
    As soon as a drone receives a message containing obstacle detection information, it updates the matrix which it stores. Detection information is dated and has an expiration date based on renewal rate, time, and speed of the swarm.
    At every moment, a drone calculates its trajectory. For example, this calculation consists in determining the direction of the instantaneous speed and the amplitude of the instantaneous speed of the drone.
    This calculation takes into account:
    the distance between the drone considered and its neighboring drones;
    the relative speed between the drone considered and its nearby drones;
    - the relative direction between the drone considered and its nearby drones;
    - the presence or absence of obstacles in the cells of the matrix towards which it moves; and,
    - the presence or absence of obstacles near its nearby drones.
    By taking into account these different variables, the drone considered maintains a distance between itself and its neighbors, which varies around the reference distance DO so as to maintain the communication link.
    Thus, in FIG. 3, the swarm 101 moves in a main direction by adopting a formation in a regular pentagon, each drone constituting a vertex of this pentagon.
    Each drone moves substantially parallel to the main direction.
    The front-facing drones monitor the environment in front of the swarm. The side drones monitor the environment on the side of the swarm. The rear drone monitors the environment towards the rear of the swarm.
    In FIG. 3, an obstacle 20 is detected by the right front drone 112.
    The drone 112 transmits the obstacle detection information to its neighbors 111, 113 and 114.
    These in turn pass on this obstacle detection information to the drone 115.
    Each drone immediately updates its environment representation matrix.
    At the same time, each drone determines the relative position and speed of nearby drones. For example the drone 114 calculates the relative position and the speed of the drones 112 and 115, or the drone 115 calculates the relative position and the speed of the drones 112 and 114
    Each drone calculates its individual trajectory by taking into account the obstacle detection information, in particular the information carried by the matrix stored in the memory of the computer 50 when such a matrix is used, and the position and / or the speed of the nearby drones.
    In particular, the drone 114, informed of the presence of the obstacle 20 detected by the drone 112, modifies its individual trajectory so as to bypass this obstacle. It moves to the left in Figure 5 and thus approaches the barycenter of the swarm.
    The drone 115 noticing the approaching of the drone 114 slows down so as to shift more towards the rear of the swarm in FIG. 5.
    The initial pentagon configuration is dynamically deformed so as to allow the swarm to bypass obstacle 20.
    Finally, in Figure 5, the swarm 101 having passed the obstacle 20, resumes its initial configuration in regular pentagon. The updated matrix of each drone is updated by resetting the cell or cells where the presence of obstacle 20 had been reported.
    VARIANTS OF EMBODIMENT
    Many variants are possible. For example, in the case of a swarm comprising a large number of drones, a priority process is advantageously implemented in the sending of messages between drones. For example, a drone scanning the environment in the direction the swarm is moving can send obstacle detection information N times more often than a drone scanning another area.
    The configuration adopted by the swarm can also change depending on the speed V of movement of the swarm. For example, when it is high, it will be necessary to know precisely the environment to which the swarm is moving. Likewise, in the event of an attack, the swarm stops and the drones are oriented so as to observe the environment in all directions in order to detect the threat.
    The swarm just presented is discreet in the sense that it requires no ground-swarm communication for the realization of the detection and avoidance functionality. It is discreet because the number of communication links is optimized. It independently manages the obstacle detection and avoidance functionality. It is made up of light drones carrying low-cost sensor systems.
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1. Swarm (1) consisting of a plurality of drones (11-17), the drones being flying drones, the drones forming between them a communication network, characterized in that the swarm implements, in autonomy, obstacle avoidance functionality (20) based on a collaborative observation of the swarm environment by each of the drones and the sharing of obstacle detection information between the drones.
    [2" id="c-fr-0002]
    2. Swarm (1) according to claim 1, in which each drone (11) embarks:
    - a sensor system (30) allowing the observation of the swarm environment inside a partial observation envelope and the generation of obstacle detection information in the event of the presence of a obstacle inside said partial observation envelope;
    - a radiocommunication means (40) for establishing at least one communication link with another swarm drone for the exchange of obstacle detection information; and
    - a calculation unit (50) suitable for calculating an individual trajectory of said drone from the obstacle detection information generated by said drone or received from another drone of the swarm.
    [3" id="c-fr-0003]
    3. Swarm (1) according to claim 2, in which the calculation unit (50) of each drone (11) is capable of determining a relative position and / or a relative speed of at least one drone close to said drone, the calculation unit of said drone calculating the individual trajectory of said drone taking into account, in addition, said relative position and / or said relative speed.
    [4" id="c-fr-0004]
    4. Swarm (1) according to claim 2 or claim 3, wherein the calculation unit (50) of each drone (11) calculates the individual trajectory of said drone so that the swarm adopts an optimized configuration.
    [5" id="c-fr-0005]
    5. Swarm (1) according to claim 4, in which the configuration is optimized by maximizing an area of the environment observed by the swarm, the observed area corresponding to the meeting of the partial observation envelopes (41 - 47) of each drone (11 - 17) of the swarm.
    [6" id="c-fr-0006]
    6. Swarm (1) according to claim 5, wherein, the swarm moving in a main direction (V), the drones (11 - 17) are oriented so that the observed area is preferably located in front of the swarm of drones.
    [7" id="c-fr-0007]
    7. Swarm (1) according to any one of claims 4 to 6, in which the configuration is optimized so that a topology of the communication network formed between them by the drones (11 - 17) of the swarm is connected , preferably biconnected.
    [8" id="c-fr-0008]
    8. Swarm (101) according to any one of claims 4 to 7, in which the swarm is able to depart from its optimized configuration by deformation to avoid an obstacle (20), then to resume the initial optimized configuration after to have overcome the obstacle.
    [9" id="c-fr-0009]
    9. A swarm (101) according to claim 7 or claim 8, in which the configuration is optimized so that a distance between two nearby drones is constrained around a reference distance (D0).
    [10" id="c-fr-0010]
    10. Swarm (1) according to any one of the preceding claims, in which the drones (11 - 17) are identical to each other, the on-board sensor systems (30) by each of the drones being identical.
    [11" id="c-fr-0011]
    11. Swarm according to any one of the preceding claims, in which the drones are different, the sensor systems on board by each of the drones being identical or different, the swarm being heterogeneous.
    [12" id="c-fr-0012]
    12. Swarm (1) according to any one of the preceding claims, in which each drone (11 - 17) is a light drone, having a total wingspan of less than one meter.
    [13" id="c-fr-0013]
    13. Swarm (1) according to any one of claims 2 to 12, in which the calculation unit (50) of a drone (11) stores a matrix (80) meshing the environment of the swarm, the matrix being subdivided into cells, each cell in which an obstacle has been detected being associated with a flag, an update of the matrix being carried out on the basis of obstacle detection information generated by said drone or received from another drone swarm.
    [14" id="c-fr-0014]
    14. Swarm (1) according to claim 13, in which the dimensions of the cells of the matrix (80) depend on the partial observation envelopes (41 - 47) of the sensor systems (30) of the drones of the swarm.
    [15" id="c-fr-0015]
    15. Method for detecting and avoiding an obstacle implemented in a swarm according to any one of claims 1 to 14, characterized in that it comprises the steps consisting in:
    - adoption by the swarm of an optimized configuration;
    10 - observation of an area of the environment corresponding to the meeting of the partial observation envelopes of each drone of the swarm;
    - sharing obstacle detection information generated by a drone with the other swarm drones using the communication network established between the swarm drones; and,
    15 - calculation by each drone of its individual trajectory, taking into account the obstacle detection information that it has generated and / or that it has received from other drones.
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    WO2019025293A1|2019-02-07|Onboard control unit for a drone system, drone and drone system comprising the onboard control unit
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    EP3571468B1|2020-07-29|Method for observing the surface of the earth and device for implementing same
    同族专利:
    公开号 | 公开日
    FR3071093B1|2022-02-11|
    EP3454316A1|2019-03-13|
    US20190080621A1|2019-03-14|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US9104201B1|2012-02-13|2015-08-11|C&P Technologies, Inc.|Method and apparatus for dynamic swarming of airborne drones for a reconfigurable array|
    WO2016053194A1|2014-10-03|2016-04-07|Infinium Robotics Pte Ltd|System for performing tasks in an operating region and method of controlling autonomous agents for performing tasks in the operating region|
    US20160368600A1|2015-06-12|2016-12-22|Sunlight Photonics Inc.|Aircraft assembly for vertical take-off and landing|
    US20170090483A1|2015-09-24|2017-03-30|Intel Corporation|Drone sourced content authoring using swarm attestation|
    US9754497B1|2017-01-27|2017-09-05|Northrop Grumman Systems Corporation|Alternate means of controlling large numbers of commercial drones over airports and populated areas|
    US9639960B1|2016-11-04|2017-05-02|Loveland Innovations, LLC|Systems and methods for UAV property assessment, data capture and reporting|FR3098600A1|2019-07-11|2021-01-15|Dassault Aviation|RADAR SYSTEM AND ASSOCIATED RADAR DETECTION METHOD|
    CN110450947A|2019-08-28|2019-11-15|华东师范大学|A kind of unmanned plane of automatic obstacle avoiding|
    US11064037B2|2019-11-15|2021-07-13|International Business Machines Corporation|Specifying element locations within a swarm|
    DE102020000663A1|2020-01-31|2021-08-05|Mbda Deutschland Gmbh|Method for improving a navigation quality by actively designing a movement formation of a collaborative swarm of mobile unmanned units|
    DE102020203054B4|2020-03-10|2021-12-09|Airbus Defence and Space GmbH|Method for controlling a formation of a cooperating swarm of unmanned mobile units|
    CN112134607A|2020-06-10|2020-12-25|合肥工业大学|Rapid reconstruction method and system for unmanned aerial vehicle cooperative relay network in emergency|
    法律状态:
    2019-03-15| PLSC| Publication of the preliminary search report|Effective date: 20190315 |
    2019-09-30| PLFP| Fee payment|Year of fee payment: 3 |
    2020-09-30| PLFP| Fee payment|Year of fee payment: 4 |
    2021-09-30| PLFP| Fee payment|Year of fee payment: 5 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1700905A|FR3071093B1|2017-09-08|2017-09-08|SWARM CONSISTS OF A PLURALITY OF LIGHT FLYING DRONES|
    FR1700905|2017-09-08|FR1700905A| FR3071093B1|2017-09-08|2017-09-08|SWARM CONSISTS OF A PLURALITY OF LIGHT FLYING DRONES|
    EP18193055.3A| EP3454316A1|2017-09-08|2018-09-06|Swarm composed of a plurality of light flying drones|
    US16/125,658| US20190080621A1|2017-09-08|2018-09-07|Swarm consisting of a plurality of lightweight drones|
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