Patent Application
20240346938
The present application claims benefit from IL285486 filed on Aug. 9, 2021.
The invention is in the field of generating a flight path for an aerial vehicle.
A flight path defines the path to be followed by an aerial vehicle. The flight path depends on various constraints of the mission to be performed by the aerial vehicle.
References considered to be relevant as background to the presently disclosed subject matter are listed below (acknowledgement of the references herein is not to be inferred as meaning that these are in any way relevant to the patentability of the presently disclosed subject matter):
There is now a need to propose new systems and methods of generating a flight path for an aerial vehicle.
In accordance with certain aspects of the presently disclosed subject matter, there is provided a method comprising, by a processor and memory circuitry (PMC), for an aerial vehicle comprising a payload operative to perform an interaction with a target: for each target of a plurality of targets, determining an interaction area based on a position of the target, wherein, for each position of the aerial vehicle located in the interaction area of the target, the interaction between the payload and the target is enabled according to an operability criterion, generating a series of connections, wherein each connection comprises at least one waypoint located in an interaction area of a target of the plurality of targets and at least one waypoint located in an interaction area of another different target of the plurality of targets, wherein each interaction area comprises a waypoint of at least one connection of the series of connections, and obtaining a flight path for the aerial vehicle using the series of connections.
In addition to the above features, the method according to this aspect of the presently disclosed subject matter can optionally comprise one or more of features (i) to (xxi) below, in any technically possible combination or permutation:
In accordance with other aspects of the presently disclosed subject matter, there is provided a system comprising a processor and memory circuitry (PMC) configured to perform, for an aerial vehicle comprising a payload operative to perform an interaction with a target, the method as described above.
In accordance with other aspects of the presently disclosed subject matter, there is provided a non-transitory storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform, for an aerial vehicle comprising a payload operative to perform an interaction with a target, the method as described above.
In accordance with other aspects of the presently disclosed subject matter, there is provided an aerial vehicle comprising a payload operative to perform an interaction with a target and a processor and memory circuitry (PMC) configured to perform the method as described above.
According to some embodiments, the proposed solution is able to generate automatically an optimized flight path for an aerial vehicle.
According to some embodiments, the proposed solution generates an optimized flight path for an aerial vehicle without requiring intervention of an operator.
According to some embodiments, the proposed solution generates a flight path for an aerial vehicle which enables acquisition of a plurality of targets by an imaging device of the aerial vehicle.
According to some embodiments, the proposed solution improves operational performance of an aerial vehicle, such as a UAV.
According to some embodiments, the proposed solution optimizes the length of the flight path while taking into account the level of priority of the targets to be acquired.
According to some embodiments, the proposed solution generates the flight path in real time or quasi real time.
According to some embodiments, the proposed solution enables the aerial vehicle to perform an acquisition of targets while avoiding forbidden areas.
According to some embodiments, the proposed solution computes an optimized flight path without requiring intensive usage of processing resources.
According to some embodiments, the proposed solution generates an optimized flight path for acquiring targets, even if the targets are mobile.
In order to better understand the subject matter that is disclosed herein and to exemplify how it may be carried out in practice, embodiments will now be described, by way of non-limiting example only, with reference to the accompanying drawings, in which:
In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the presently disclosed subject matter may be practiced without these specific details. In other instances, well-known methods have not been described in detail so as not to obscure the presently disclosed subject matter.
The term “processor and memory circuitry” (PMC) as disclosed herein should be broadly construed to include any kind of electronic device with data processing circuitry, which includes for example a computer processing device operatively connected to a computer memory (e.g. digital signal processor (DSP), a microcontroller, a field programmable gate array (FPGA), and an application specific integrated circuit (ASIC), etc.) capable of executing various data processing operations.
Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as “using”, “generating”, “determining”, “obtaining”, “transmitting”, “dividing”, “comparing” or the like, refer to the action(s) and/or process(es) of a processor and memory circuitry that manipulates and/or transforms data into other data, said data represented as physical, such as electronic, quantities and/or said data representing the physical objects.
It can encompass a single processor or multiple processors, which may be located in the same geographical zone or may, at least partially, be located in different zones and may be able to communicate together.
Embodiments of the presently disclosed subject matter are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the presently disclosed subject matter as described herein.
The invention contemplates a computer program being readable by a computer for executing one or more methods of the invention. The invention further contemplates a machine-readable memory tangibly embodying a program of instructions executable by the machine for executing one or more methods of the invention.
Attention is drawn to
An aerial vehicle 100 includes a payload 105 operative to perform an interaction with at least one target.
The aerial vehicle 100 corresponds e.g. to an aircraft, a helicopter, a UAV (unmanned aerial vehicle), a balloon, etc.
The UAV can be fully autonomous or can be controlled by an operator located at a remote central station, or is both controlled remotely and operates autonomously.
According to some embodiments, payload 105 is operative to acquire a target. In some embodiments, payload 105 includes an imaging device (e.g. a camera), a radar, a LIDAR, etc.
According to some embodiments, payload 105 is operative to perform a physical interaction (e.g. destructive interaction) with the target (and not only a remote acquisition). For example, payload 105 includes a laser operative to remove material from the target, a device enabling launch of a projectile to annihilate the target, etc.
Although reference will be made hereinafter to the acquisition of a target by the payload, it is to be understood that this is not limitative, and other interactions can be performed with the target(s), as explained above.
The aerial vehicle 100 comprises aircraft positioning and sensing utilities 110 such as air speed detector (e.g. Pitot tube), GPS receiver, inertial navigation system (INS), altimeter (e.g. pressure altimeter, sonic altimeter, radar altimeter, GPS based altimeter, etc.), etc. These devices are used for determining aircraft situation data including: current position and attitude (six degrees of freedom), heading, and speed of the aerial vehicle.
The aerial vehicle 100 comprises aerial control devices 120 which include, for example, elevators, ailerons, flaps, rudder, throttle, wheels, and others. Elevators enable the plane to go up and down through the air. The elevators change the horizontal stabilizer's angle of attack, and the resulting lift either raises the rear of the aircraft (pointing the nose down) or lowers it (pointing the nose skyward). Ailerons are horizontal flaps located near the end of an airplane's wings. Ailerons allow one wing to generate more lift than the other, resulting in a rolling motion that allows the plane to bank left or right. A rudder is a flap located on the vertical tail wing. The rudder enables the plane to turn left or right. Throttle enables to increase/decrease thrust. Wheels may be used during landing.
The aerial vehicle 100 comprises a flight computer 120 (including a PMC), which is configured to control and manage the operations of various sub-systems and devices on-board the aerial vehicle 100 during a mission.
Flight computer 101 can control sub-systems related to takeoff and landing, navigation, payload activation, etc. In particular, flight computer 101 controls various aerial control devices 120 for the purpose of controlling the motion of the aerial vehicle 100 along a flight path.
A flight path (also called flight route) defines the path to be followed by the aerial vehicle 100 during its mission. The flight path can comprise a series of points (also called waypoints (WPs)) defining the path of the aerial vehicle. Each waypoint can comprise coordinates (e.g. latitude/longitude—in some embodiments, each waypoint can also comprise an altitude).
In some embodiments, the flight path is defined by a trajectory to be followed by the aerial vehicle, and, in particular, by a series of connections joining a series of waypoints.
According to some embodiments, the flight path is generated by a navigation computer 130 embedded on the aerial vehicle 100. The navigation computer 130 comprises a processor and memory circuitry.
According to some embodiments, the flight path is generated by another entity communicating with the aerial vehicle 100. For example, a remote control unit 160 (which comprises a PMC) generates the flight path and communicates the flight path to the aerial vehicle 100, using remote communication (e.g. radio communication, satellite communication, etc.).
In some embodiments, an operator uses the remote control unit 160 to transmit commands to the aerial vehicle 100. These commands can include e.g. navigation commands, control of an operation of the payload 105, etc.
According to some embodiments, the flight path is generated both by the navigation computer 130 and by the remote control unit 160.
According to some embodiments, at least one acquisition and/or tracking device 170 is operative to acquire data informative of a plurality of targets. Device 170 include e.g. a radar, a camera, COMINT (communications intelligence) sensor, ELINT (electronic intelligence) sensor, AIS, a device providing input to the aircraft or to the remote control unit, etc. As explained hereinafter, device 170 can e.g. determine (or at least estimate) position of the targets (in particular, position over time), velocity of the targets, a dimension of the targets (e.g. a size of the target), etc. In some embodiments, position and/or velocity and/or dimensions of one or more targets are provided automatically by a sensor and/or manually by an operator (e.g. to the aerial vehicle 100 and/or to the remote control unit 160).
According to some embodiments, device 170 can track one or more targets over time. In some embodiments, device 170 can predict the trajectory of targets over time.
According to some embodiments, device 170 can communicate data with the aerial vehicle 100 and/or with the remote control unit 160.
Attention is now drawn to
According to some embodiments, at least some of the targets 2001 to 200N are located at sea (in some embodiments, each target includes at least a part which is located above sea level). The targets at sea can include e.g. marine vessels, icebergs, buoys, etc. These examples are not limitative.
According to some embodiments, at least some of the targets 2001 to 200N are located on ground. This can include for example a ground vehicle, a person, a building, etc. These examples are not limitative.
According to some embodiments, at least some of the targets 2001 to 200N are located in the air. This can include for example an aircraft, a UAV, a balloon, a helicopter, etc. These examples are not limitative.
According to some embodiments, at least one of targets 2001 to 200N is a static target (meaning that the position is fixed and does not vary over time).
According to some embodiments, at least one of targets 2001 to 200N is a mobile target (meaning that its position varies over time).
According to some embodiments, the mission of the aerial vehicle 100 comprises acquiring, using its payload 105, all targets 2001 to 200N (or at least a subset of these targets 2001 to 200N).
In order to perform this mission, a flight path is to be generated for the aerial vehicle 100. As explained hereinafter, in some embodiments, the flight path is periodically updated, since at least some of the targets are mobile over time.
Attention is now drawn to
Assume that the mission requires acquisition of targets 2001 to 200N.
According to some embodiments, a flight path is generated for the aerial vehicle 100 during the flight of the aerial vehicle 100. Assume that at a period of time Ti (as explained hereinafter, in some embodiments, the method is iterative—at the first iteration, i=1), the aerial vehicle 100 has a position Paerial, i.
The method includes, for each target of the plurality of targets 2001 to 200N (or for at least some of them), determining (operation 300) an interaction area 2101 to 210N.
The interaction area is an area for which, for each position (latitude/longitude) of the aerial vehicle 100 located within the interaction area, the interaction between the payload 105 of the aerial vehicle 100 and the target is enabled according to an operability criterion.
Assume for example that the mission requires acquisition of a target 200j. As a consequence, if the aerial vehicle 100 has a position in the interaction area 210j (note that the interaction area 210j includes both an interior area 211j of the interaction area 210j and a boundary 212j of the interaction area 210j), its payload 105 can acquire the target 200j. To the contrary, if the aerial vehicle 100 has a position which is outside the interaction area 210i (note that a position on the boundary 212j is considered as being in the interaction area 210j), its payload 105 cannot acquire the target 200j.
The operability criterion can define e.g. a quality parameter/a threshold (such as a signal to noise ratio, a resolution, a relative size of the target with respect to the frame, etc.) for which it can be considered that the payload 105 is able to acquire the target. Below this threshold, it can be considered that the payload 105 is not able to acquire the target (e.g. because the resolution and/or the signal to noise ratio and/or the relative size of the target in the image is too low, etc.).
According to some embodiments, the operability criterion can be different for each target. For example, for sensitive targets, a harsher threshold is imposed (meaning that for a given size of a target, the interaction area will be of smaller size), whereas for low sensitive targets, a relaxed threshold is imposed (meaning that for a given size of a target, the interaction area will be of larger size).
According to some embodiments, the size of the interaction area does not depend on the altitude of the aerial vehicle 100 (meaning that for conventional altitudes of the aerial vehicle 100, the interaction area remains substantially identical). For example, for a target located at sea, since the sea area is generally free of obstacles, the altitude of the aerial vehicle 100 does not substantially impact the size of the interaction area.
In some embodiments, altitude of the aerial vehicle 100 can impact the size of the interaction area. Indeed, in crowded areas (such as in a city), obstacles can be present between the line of sight of the payload 105 of the aerial vehicle flying at a given altitude, and the target. Assume that without any obstacles, the interaction area would have a radius R1. In order to take into account that obstacles are present for an aerial vehicle 100 flying at this altitude, the interaction area can be voluntary reduced to have a radius R2, with R2<R1. The coefficient of reduction can be determined e.g. using simulations (a simulation of the payload and of the crowded area including the target to be acquired can be performed), or can be predefined, or can be determined using e.g. heuristics.
According to some embodiments, determination of the interaction area for a target can be performed using the method of
The method can include (operation 400) obtaining data informative of a position of the target at the period of time Ti.
According to some embodiments, the target itself communicates its position. For example, for a sea target, the target can embed an automatic identification system (AIS). For a ground target, the target can embed e.g. a GPS system and a transponder for communicating its position. These examples are however not limitative.
According to some embodiments, the position of the target can be determined by the acquisition and/or tracking device 170 (e.g. a radar).
Note that position of the target can be either static (and in this case it is sufficient to determine this position once) or can evolve over time (and in this case this position needs to be determined periodically). The period at which this position needs to be determined depends in particular on the relative velocity of the target with respect to the aerial vehicle 100.
The method includes (operation 410) obtaining data informative of a dimension of the target. This data can include e.g. an estimated size of the target. In some embodiments, this data can include an estimated height, length and width of the target.
In some embodiments, the data informative of dimension of the target can be determined by the acquisition and/or tracking device 170. Generally, it is sufficient to acquire this data once. In some specific cases, the size of the target can evolve over time, and this data can be acquired periodically.
The method further includes (operation 420) using data informative of a position of the target and data informative of a dimension of the target to determine the interaction area of the target at the period of time Ti.
According to some embodiments, the interaction area is a disk (the center of the disk corresponds to the position of the target at the period of time Ti). The radius of the disk defines the maximal distance at which the payload 105 of the aerial vehicle 100 can be located from the target and can still be able to acquire the target. When the aerial vehicle 100 is located at the boundary of the interaction area (in the case of a disk, this corresponds to the perimeter of the disk), its payload 105 can still acquire the target. When the aerial vehicle 100 is located out of the interaction area, its payload 105 cannot acquire the target (even if some kind of acquisition is possible, even at long range, this acquisition will not meet the operability criterion).
Although the interaction area is depicted as a disk, in some embodiments, it can have another shape (for example because there is a forbidden area, or because of other constraints provided e.g. by an operator).
Note that the ability of the payload 105 to acquire the target depends mainly on the distance between the target and the aerial vehicle 100 and on the size of the target.
According to some embodiments, other parameters (such as weather conditions) which can influence the ability of the payload 105 to acquire the target, are neglected. In other embodiments, a model which models impact of the weather conditions on the ability of the payload to 105 to acquire the target can be used to determine the interaction area.
According to some embodiments, when the payload 105 is an acquisition device, the interaction area of each target is determined based on a maximal zoom-in capability of the acquisition device. The maximal zoom-in capability defines also the minimal field of view of the acquisition device.
For example, assume that the mission requires that each target has to be acquired by the acquisition device such that each target fills 20% of the size of the frame of the acquisition device.
If the target has a length of 100 m, a frame covering an area of 500 m is required (since 100/0.2=500).
If it is known that the minimal field of view of the acquisition device (as mentioned the minimal field of view and the maximal zoom-in capability are equivalent) is 1 degree (0.017 rad), this means that the radius of the interaction area for this target is 30 km (500/0.017≈30 km—the formula which can be used is e.g.: Length of the target/Field of view=Radius of the interaction area).
The use of the maximal zoom-in is not mandatory and other parameters can be used.
For example, if the payload 105 is a laser, the maximal effective distance of the laser can be used to determine the radius of the interaction area (the maximal effective distance is the maximal distance to the target for which the laser can perform an interaction with the target—above this distance the interaction cannot be performed by the laser, or the interaction does not he meet an operability criterion).
Reverting to
In particular, each connection includes at least one waypoint located in an interaction area of a target of the plurality of targets, and at least one waypoint located in an interaction area of another different target of the plurality of targets.
For example, assume that a connection includes at least one waypoint located in an interaction area of a first target, and at least one waypoint located in an interaction area of a second target (different from the first target).
As a consequence, when the trajectory of the aerial vehicle 100 follows a path along this connection, its payload 105 will be able to acquire the first target and the second target.
According to some embodiments, each connection is an oriented connection (that is to say, it comprises a first waypoint corresponding to the starting point, and a second waypoint corresponding to the endpoint of the connection, the connection being oriented from the first waypoint to the second waypoint).
In order to be able to acquire all targets of the plurality of targets, each interaction area of each target of the plurality of targets includes a waypoint of at least one connection of the series of connections. In other words, the series of connections is such that each interaction area is intersected by at least one connection of the series, thereby enabling acquisition of all targets by the payload 105 of the aerial vehicle 100.
As explained hereinafter, according to some embodiments, the series of connections is generated progressively (by connecting the various targets progressively) by testing various alternatives so as to meet an optimization criterion.
Once the series of connections has been generated, a flight path FPi is obtained (operation 320), which corresponds to the union of this series of connections.
According to some embodiments, operations 300, 310 and 320 are performed during a flight of the aerial vehicle.
If at least one target of the plurality of targets is a moving target, then the flight path FPi can be updated over time, to take into account this evolution.
This is illustrated in
At the period of time Ti+1, the position of the aerial vehicle 100 and of the one or more moving targets has changed. The position of the static targets has not changed. Therefore, a different series of connections is obtained at iteration i+1, which is used to generate a different flight path FPi+1 for time Ti+1.
Note that according to some embodiments, at each iteration “i”, generating the series of connections can rely on an assumption that the targets are all static (until update of the flight path at iteration “i+1”).
For example, assume that the area 250 in which the targets are located has a dimension of X (e.g. length of X). Assume that during the period of time “Ti+1−Ti”, the distance traveled by each moving target 200 of the plurality of targets is Dj (this can be calculated using the velocity of each moving target), and Dj can be ignored with respect to X (|Dj/X|≤threshold T−the threshold T for which Dj can be selected with respect to X can be set e.g. by an operator). In a non-limitative example, assume that X is equal to 200 km and D is equal to 2 km, the threshold can be set as T=D/X=2/200=0.01 (this value is not limitative). In this example, generation of the connections at each iteration “i” can rely on the assumption that each target is static.
According to some embodiments, the velocity of the moving target(s) is not known or not measured. At each iteration of the method, each target can be modelled as static. In some embodiments, the frequency of update of the flight path can be increased to take into account the fact that one or moving target(s) may have a velocity which cannot be ignored with respect to the dimension of the area 250 to be covered by the aerial vehicle 100.
According to some embodiments, the frequency of update (F) can be determined using the following formula (this formula is not limitative): F=D/target speed. D can be obtained as follows: D=T·X (with T the threshold as defined above and X the size of the area as defined above). The “target speed” corresponds to the speed of the target which is to be handled. In some embodiments, if a plurality of moving targets is to be handled within the area, the following equation can be used: F=D/max speed, wherein max speed is the maximal speed of the plurality of moving targets that need to be handled.
According to some embodiments, at a given period of time, the flight path is determined for all targets (although, in practice, the flight path will be updated before the aerial vehicle will interact with all targets) since this information can be useful to provide indications such as current estimated time to interact with all targets during the mission, amount of fuel required to perform the whole mission, etc. In some embodiments, the flight path is determined only for some of the targets.
According to some embodiments, and as explained hereinafter, at each iteration of the method, the velocity of the moving target(s) can be taken into account to generate the flight path.
According to some embodiments, when the aerial vehicle 100 is located in an interaction area of a given target of the plurality of targets, it can automatically provide information on the target which is pertinent for the mission. For example, assume that the payload 105 is an acquisition device and that the target is a marine target (this is not limitative). The aerial vehicle 100 can determine whether data of the marine target (e.g. size, name, flag, which can be determined based on an image of the marine target acquired by the payload 105) matches data provided by an AIS of the marine target. If the aerial vehicle 100 fails to automatically identify the marine target, the method can include entering a mode in which the aerial vehicle 100 is forced to fly towards the target. Then, an operator, located e.g. at the remote control unit 160, attempts to manually identify the target based on images acquired by the payload 105 of the aerial vehicle 100. Once the aerial vehicle 100 has been identified, the aerial vehicle 100 can return to an automatic mode (the flight path can be updated based on the last position of the aerial vehicle 100, using e.g. the method of
Attention is now drawn to
According to some embodiments, in order to generate the series of connections (see operation 310), the method comprises a preliminary operation 501 of dividing the plurality of targets into a plurality of clusters (5001, 5002, . . . ,500N). At least one cluster of the plurality of clusters includes at least two targets. The other clusters can include one target or a plurality of targets.
The division into clusters can depend on a distribution of distance between the targets. For example, targets belonging to the same given cluster are such that the distance inter-targets within this given cluster is (e.g. on average) lower than the distance between targets of this given cluster to other targets belonging to other clusters. In some embodiments, a size of the area 250 can be taken into account.
Division into clusters can use e.g. clustering algorithms such as K-means, Mean-Shift Clustering, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), EMGMM (Expectation-Maximization Algorithm for Gaussian mixture model), HAC (hierarchical agglomerative clustering), etc.
Once the clusters have been determined, an order (operation 510) between the clusters can be determined. For example, the order can indicate that the flight path of the aerial vehicle 100 should first go to cluster 2 and then to cluster 1, up to cluster N.
Note that according to some embodiments, the clusters and/or the order between the clusters can evolve over time, since one or more targets can be a moving target. Therefore, at each time Ti, operations 501 and 510 can be repeated.
Various criteria can be used to determine the order between the clusters. In some embodiments, a score can be attributed to each cluster based on the various criteria, and, based on this score, the order between the clusters can be determined (for example, the higher the score of a given cluster, the higher the probability that this given cluster corresponds to the first cluster).
According to some embodiments, a distance between a center of mass of each cluster and an initial position from which the flight path is to be generated (e.g. position of the aerial vehicle 100 at the period of time Ti) is used to determine the order. The center of mass can correspond e.g. to a centroid/center of gravity determined as an average of all positions of the targets within the cluster. In the example of
According to some embodiments, a number of targets in each cluster is taken into account. The larger this number for a cluster, the higher the score attributed to this cluster. Therefore, this cluster will have a higher chance to be among the first clusters in the order. This reflects the fact that a cluster including a larger number of targets is of higher interest than a cluster with a lower number of targets, and therefore should be located beforehand along the flight path.
According to some embodiments, assume that each target is assigned with a level of priority. The level of priority indicates to which extent acquisition of the target is important in the mission of the aerial vehicle 100 (or, more generally, it reflects importance of interaction with the target). For example, a high level of priority indicates that acquisition of the target is of high importance.
An aggregated level of priority can be computed for each cluster. For example, this aggregated level of priority can be computed as an average of all levels of priority of all targets within the cluster. This is however not limitative.
Therefore, the aggregated level of priority of each cluster can be taken into account when determining the order between the clusters. The higher the aggregated level of priority of a cluster, the higher the score attributed to this cluster. Therefore, this cluster will have a higher chance to be among the first clusters in the order.
Based on one or more of the criteria discussed above (and/or additional/different criteria), the order between the clusters can be determined.
According to some embodiments, the score based on which the order between the clusters is determined can be calculated using the formula (this formula is not limitative):
Scorecluster=(ClusterAveragePriority*ClusterNumofTargets)/(ClusterDistance)
In this formula, Scorecluster is the score of a given cluster, ClusterAveragePriority is the aggregated level of priority of the targets of the given cluster (as explained above), ClusterNumofTargets is the number of targets of the given cluster (as explained above) and ClusterDistance is the distance to the given cluster (as explained above).
Note that the order between the clusters can evolve over time. Similarly, division of the targets into clusters can evolve over time. Therefore, according to some embodiments, the division into clusters and the determination of the order between the clusters is repeated at each period of time (Ti, Ti+1, etc.).
Attention is now drawn to
The method can include determining (operation 601), among the plurality of targets, a target which is the first target to be acquired by the aerial vehicle 100 along its flight path.
Operation 601 can include determining a connection which includes the current position of the aerial vehicle 100 (at time Ti) and a waypoint located e.g. at the boundary of an interaction area of a target, such that this connection meets an optimization criterion. According to some embodiments, the connection is selected to be orthogonal to a tangent of the boundary of the interaction area of the target (at this waypoint).
According to some embodiments, the optimization criterion takes into account the length of the connection. In other words, the target for which the connection has the smallest length has the highest probability to be selected as the first target. Note that the connection can be a straight line. This is however not mandatory, because in some embodiments, there can be one or more forbidden areas (a forbidden area is an area in which it is forbidden for the aerial vehicle to enter). As a consequence, the connection can include various pieces of connected straight lines, or one or more curved portions enabling bypass of the forbidden area(s).
According to some embodiments, the optimization criterion takes into account (in addition to, or in place of the length of the connection) the level of priority of each target. In other words, it is possible that a target which is located farther than another target with respect to the current position of the aerial vehicle, will be selected as the first target because it has a higher level of priority, although the length of the connection to reach the interaction area of this target is larger.
According to some embodiments, the optimization criterion takes into account both the length of the connection to the target and the level of priority of the target.
An example is provided with reference to
Assume that the area includes targets 6001 to 600N, associated with interaction areas 6101 to 610N (each interaction area 6101 to 610N has a boundary 6121 to 612N).
According to some embodiments, a plurality of candidate connections 6131 to 613N is generated (operation 601 in
A plurality of candidate connections 6201 to 620N is obtained (in order to simplify presentation of
Based on the candidate connections, a first target is selected.
Assume for example that the optimization criterion takes into account only the length of the connection. As a consequence, in the example of
According to some embodiments, the targets are divided into clusters (see
According to some embodiments, if the targets have been divided into a plurality of clusters, a flight path can be first generated for the targets of the first cluster. In some embodiments, the order between the targets of the first cluster is selected according to a decreasing distance with respect to the next cluster (e.g. center of mass of the second cluster).
For example, the target which is selected as the first target of the flight path within the first cluster is the target which has the highest distance to the next cluster (in this case the second cluster).
The target which is selected as the second target of the flight path within the first cluster is the target which has the second highest distance to the next cluster (in this case the second cluster).
The last target of the flight path within the first cluster is the target which is the closest to the second cluster. This enables to have a transition between each cluster and the consecutive cluster with the smallest travelling distance.
In some embodiments, the level of priority of the targets can be also taken into account to determine the order between the targets within each cluster.
This process can be repeated similarly for each cluster.
For the last cluster, since there is no next cluster, the targets are ordered according to the smallest distance with respect to the current position on the flight path.
The method described above is not limitative, and in some embodiments, for each cluster, the targets are ordered according to the smallest distance with respect to the current position on the flight path.
Attention is drawn to
Once the first target has been identified, the method can include determining the second target of the flight path.
According to some embodiments, the method of
The difference is that the starting point is not the current position of the aerial vehicle 100 at time Ti, but rather the waypoint C1,2 corresponding to the extremity of the previous connection C1 (determined in the method of
The method includes determining a second target, for which a second candidate connection C2 meets an optimization criterion. The second candidate connection C2 comprises the waypoint W1,2 (determined at the previous iteration of the method) and a waypoint W2,1 located at a boundary of the interaction area of the second target. The second candidate connection C2 is orthogonal to a tangent to the boundary of the interaction area of the second target (at the waypoint W2,1).
As explained with reference to
In the example of
The method of
According to some embodiments, and as explained hereinafter, different types of connections can be tested (e.g. which are not necessarily orthogonal to a tangent to a boundary of an interaction area of the target), in order to further improve generation of the series of connections.
Attention is now drawn to
According to some embodiments, once at least two consecutive targets (noted as first target and second target—note that these two targets are not necessarily the two first targets within the flight path and can correspond to any of two consecutive targets within the flight path) have been identified (see operation 660), different types of connections can be tested.
Assume (see operation 665) that a first series of connections comprising a first connection C1 and a second connection C2 have been obtained (as explained above).
The first connection C1 comprises a waypoint W1,1 (corresponding e.g. to the current position of the aerial vehicle 100 at time Ti—or corresponding to the extremity of the previous connection which connects the interaction area of the previous target to the interaction area of the first target), and a waypoint W1,2, wherein the first connection C1 is orthogonal to a tangent to a boundary 6121 of an interaction area 6101 of the first target 6001.
The second connection C2 comprises the waypoint W1,2 corresponding to the extremity of the previous connection, and a waypoint W2,1, wherein the second connection C2 is orthogonal to a tangent to a boundary 6122 of an interaction area 6102 of the second target 6002.
The method comprises generating a second series of connections (operation 665).
The second series of connections comprises a first candidate connection C′1 comprising the waypoint W1,1 and a waypoint W′1,2 located at a boundary of the interaction area 6101 of the first target 6001, wherein the first candidate connection C′1 is tangent to the boundary of the interaction area 6101 of the first target 6001 at said waypoint W′1,2.
The second series of connections comprises a second candidate connection C′2, which comprises the waypoint W′1,2 and another waypoint W′2,1 located at the boundary of the interaction area 6102 of the second target 6002, wherein the second candidate connection C′2 is orthogonal to a tangent of the interaction area 6102 of the second target 6002.
In other words, instead of requiring the aerial vehicle 100 to fly along a flight path orthogonal to the boundary of the interaction area of the first target, an approach in which the flight path is tangent to the boundary of the interaction area of the first target is evaluated.
According to some embodiments, the method comprises comparing (operation 670) the first series of connections with the second series of connections. According to some embodiments, if the length of the second series of connections is smaller than the length of the first series of connections, the method can include using the second series of connections when generating the series of connections, instead of the first series of connections.
In other words, it is tested whether the approach in which the flight path is tangent to the boundary of the interaction area of the first target is more optimal than an approach orthogonal to the tangent to the boundary of the first interaction area.
Attention is now drawn to
Assume that during generation of the series of connections for a given period of time Ti (using e.g. one of the methods described above—as mentioned above, generation of the series of connections is performed progressively, by identifying progressively the next target to be reached), it has been determined that target 600j+1 should be consecutive to target 600j in the flight path. In other words, the series of connections requires that the aerial vehicle 100 first interacts with target 600j and then with target 600j+1 (operation 680).
Assume for example that a first series of connections including connections C″1 and C″2 have been determined (see
The interaction area 610j comprises a boundary 612j (perimeter of the disk) and an interior area 611j (interior of the disk, excluding the perimeter).
Similarly, the interaction area 610j+1 comprises a boundary 612j+1 (perimeter of the disk) and an interior area 611j+1 (interior of the disk, excluding the perimeter).
As mentioned above, various types of connections can be tested (e.g. orthogonal to the boundary of the interaction area, tangent to the boundary of the interaction area, etc.).
The method comprises determining (681) a candidate connection which intersects an interior area of the interaction area of the first target and/or an interior area of the interaction area of the second target. In other words, it is tested whether flying directly through the interior area of the respective interaction areas provides a shorter flight path (than the flight path previously generated).
In the non-limitative example of
The candidate connection is compared to the connection(s) previously determined (in particular, a comparison of their respective length is performed). In the example of
Although the example of
Attention is now drawn to
According to some embodiments, the method includes obtaining (operation 700) at least one forbidden area 704. A forbidden area is an area in which it is forbidden for the aerial vehicle 100 to enter (due e.g. to regulations, tactical reasons, etc.). The forbidden area can include e.g. a series of waypoints defined by their latitude and longitude (and, if necessary, altitude).
The method includes generating (operation 710) a series of connections (using the various embodiments described above), wherein each connection of the series of connections does not comprise any waypoint located in the forbidden area(s) 704. In other words, a flight path which bypasses the forbidden area(s) is built.
Generating a connection between two interaction areas of two different targets which avoids at least one forbidden area can rely on various methods. In some embodiments, the method described in the U.S. patent application Ser. No. 16/892,726 of the Applicant (content of this patent application is incorporated hereinafter in its entirety) can be used. This is however not limitative, and other methods can be used.
A first connection C11 is generated between the current position of the aerial vehicle 100 (at time Ti) and a waypoint C111 located at a boundary of the interaction area 710j of target 700j.
If there is no forbidden area, and the method of
Note that the connection C220 is orthogonal to a tangent to the boundary of the interaction area 710j+1 of the target 700j+1, in compliance with the method of
Although in the example of
Attention is now drawn to
Assume that for given period of time Ti, a series of connections have been determined.
The method of
As a consequence, the method includes generating (operation 810) an updated series of connections. In particular, this updated series of connections does not comprise the given connection (identified as irregular because of its excessive length). In addition, the updated series of connections is selected to have a total length which is smaller than the total length of the original series of connections. In some embodiments, operation 810 comprises reusing the same waypoints, but connected in a different manner (using different connections—the waypoints can be connected in a different order).
A non-limitative example is provided in
Assume that a series of connections have been generated. Each connection defines the flight path between a starting waypoint and an ending waypoint (see waypoints 8001 to 800N). In this non-limitative example, the connections are substantially straight lines. The flight path starts from waypoint 8001 and ends at waypoint 8007.
The average length of the connections depicted in the upper part of
As a consequence, it is attempted to generate an updated series of connections. According to some embodiments, the updated series of connections (see bottom part of
Attention is now drawn to
According to some embodiments, the displacement of one or more moving target(s) can be taken into account to generate the series of connections.
Assume that the position of the aerial vehicle 100 and of the targets is known at the period of time T1 (see a non-limitative example of a map of the targets 9001 to 9007 at time T1 in
According to some embodiments, it can be determined (operation 901) that a given target among the plurality of targets meets a criterion. According to some embodiments, the given target meets the criterion if the distance between the position of the aerial vehicle 100 at time T1 and the position of the given target at time T1 is the smallest relative to all other targets. In some embodiments, the criterion can take into account the level of priority of each target, and the given target is the one which has the highest score, wherein the score depends on the distance between the aerial vehicle 100 and the given target (the lower the distance, the higher the score), and the level of priority of the given target (the higher the level of priority, the higher the score).
For example, in
The method further comprises estimating (operation 902) the period of time ΔTtarget required by the aerial vehicle 100 to reach the given target (or to reach the interaction area of the target). According to some embodiments, this estimation can be performed by assuming that the aerial vehicle 100 follows e.g. a straight line (if there is a forbidden area, then the method determines a path which avoids this forbidden area, as explained above). This can be determined since the initial position and the velocity of the aerial vehicle 100 at time T1 are known (it can be e.g. assumed that there is a constant velocity to reach the target or its interaction area), and the trajectory of each target can be predicted over time. The trajectory of each target can be predicted over time using e.g. tracking information of the device 100 (which is e.g. a radar—since the target is tracked over a period of time, its future motion can be predicted using e.g. Kalman filtering), and/or using velocity information of the target (measured by the device 100, or provided by the target itself, or by a third party).
Once ΔTtarget has been determined, the position of all targets is predicted at time T1+ΔTtarget.
Prediction of the position of the targets at a future time can be performed using various methods.
According to some embodiments, since each target can be tracked by the device 170 (e.g. a radar), a track can be generated for each target, and therefore the future position of each target can be predicted (using e.g. Kalman filters or other techniques of the art). Regarding targets which are static, their positions remain the same between T1 and T1+ΔTtarget.
At operation 904, it is verified again (at predicted time T1+ΔTtarget) whether the given target (as identified at operation 901) is still the target which is the closest to the position of the aerial vehicle 100 at time T1 (or whether the interaction area of the given target is the closest to the position of the aerial vehicle 100). Indeed, since some targets are moving towards the aerial vehicle 100, and some are moving away from the aerial vehicle 100, it can occur that a different target is the closest target at time T1+ΔTtarget.
In some embodiments, at time T1+ΔTtarget, both the distance to the aerial vehicle and the level of priority of each target is taken into account to select the target at operation 904.
In the example of
The method further includes determining an interaction area of the target selected at operation 904 (in the example of
Since the position of the selected target at time T1+ΔTtarget has been predicted, and the dimension of the selected target is known, the interaction area of the selected target located at its predicted position can be determined (using e.g. the method of
The method further includes determining a connection C300 between the position of the aerial vehicle 100 and a waypoint W301 located in the interaction area of the selected target (in the example of
The method of
The waypoint W301 is considered as the starting point, and it is determined which given target is the closest target to W301.
The time of travel ΔTtarget,2 from W301 to this given target is estimated. The positions of all targets are predicted at time T1+ΔTtarget+ΔTtarget,2. It is verified whether the given target is still the closest target to W301. If this is the case, a connection is determined between W301 and an interaction area of this given target.
The method can be repeated until the flight path is generated such that it enables acquisition of all targets. Therefore, for time T1, a complete flight path FP1 is obtained. As mentioned, in some embodiments, the flight path is updated before the aerial vehicle manages to cover all targets, but the complete flight path FP1 is useful to provide indications about estimate time to perform the mission, required fuel, etc.
Over time (e.g. at time T2 different from T1), the method of
It is to be noted that the various features described in the various embodiments may be combined according to all possible technical combinations.
It is to be understood that the invention is not limited in its application to the details set forth in the description contained herein or illustrated in the drawings. The invention is capable of other embodiments and of being practiced and carried out in various ways. Hence, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting. As such, those skilled in the art will appreciate that the conception upon which this disclosure is based may readily be utilized as a basis for designing other structures, methods, and systems for carrying out the several purposes of the presently disclosed subject matter.
Those skilled in the art will readily appreciate that various modifications and changes can be applied to the embodiments of the invention as hereinbefore described without departing from its scope, defined in and by the appended claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 285486 | Aug 2021 | IL | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/IL2022/050799 | 7/25/2022 | WO |
