JP2023019846A - Unmanned aerial vehicle, search device, search method, program, and search system - Google Patents

Abstract

The present invention provides an unmanned aerial vehicle, a search device, a search method, a program, and a search system that quickly locate a lost moving object. A search system 100 includes a search area setting unit 11 that sets a search area based on a lost location of a lost mobile object 30 and movement status information of the mobile object 30 before the loss; The node setting unit 12 sets a plurality of nodes according to the area of the object, and calculates the initial expectation level to be set for each node before flight based on the lost position and the moving direction of the moving object 30 before the loss. and an adjustment unit that adjusts the expectation level set for each node based on the radio field intensity of the radio waves received by the search unmanned aerial vehicle 20 and the position and altitude at which the radio waves were received. 15, and a flight route generation unit 14 that generates a flight route using the nodes selected based on the expectation level. [Selection diagram] Figure 1

Description

The present invention relates to an unmanned aerial vehicle, a search device, a search method, a program, and a search system for searching for a lost mobile object.

When an unmanned aerial vehicle (for example, a drone) is lost, for example, when the unmanned aerial vehicle crashes, a battery mounted on the unmanned aerial vehicle may catch fire, resulting in a disaster. Therefore, when an unmanned aerial vehicle crashes, it is necessary to quickly find the crashed unmanned aerial vehicle and prevent the occurrence of a disaster.

Patent Literature 1 discloses a technique for quickly identifying the position of an unmanned aerial vehicle in order to ensure safety when an abnormality occurs. According to the technique of Patent Document 1, when an abnormality such as a crash of the unmanned aerial vehicle is detected, a transmitter is mounted that wirelessly outputs a signal for identifying the position of the power storage device mounted on the unmanned aerial vehicle. .

JP 2019-202633 A

However, the technique of Patent Document 1 outputs a signal wirelessly from a transmitter, but does not disclose a method for searching for a crashed unmanned aerial vehicle. Therefore, it is not possible to quickly find the crashed unmanned aerial vehicle, so it is not possible to prevent disasters from occurring.

An object of the present invention is to provide an unmanned aerial vehicle, a search device, a search method, a program, and a search system for quickly searching for a lost moving object.

To achieve the above objectives, an unmanned aerial vehicle for searching lost mobile objects in one aspect:
a receiving unit that receives radio waves transmitted from a transmitter provided in the lost moving object;
a measuring unit that measures the position and altitude at which the unmanned aerial vehicle for searching is flying;
a control unit that controls the flight of the unmanned aerial vehicle for searching in a preset search area using a flight route for flying in an area where the lost mobile object is highly expected to exist;
characterized by having

Also, in order to achieve the above object, the search device in one aspect includes:
setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; a search area setting unit;
a node setting unit that sets a plurality of nodes by dividing the search area according to the size of the search area;
An expectation calculation unit that calculates an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile before communication with the lost mobile is lost. and,
an adjustment unit that, after flight, adjusts the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
a flight route generation unit that selects a node based on the degree of expectation and generates a flight route using the selected node;
characterized by having

In addition, in order to achieve the above purpose, the search method in one aspect is
the computer
setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; a search area setting step;
a node setting step of dividing the search area and setting a plurality of nodes according to the size of the search area;
An expectation calculation step of calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile before communication with the lost mobile is lost. and,
an adjustment step of, after the flight, adjusting the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
a flight route generation step of selecting nodes based on the degree of expectation and generating a flight route using the selected nodes;
characterized by having

In addition, in order to achieve the above purpose, the program in one aspect is
to the computer,
setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; a search area setting step;
a node setting step of dividing the search area and setting a plurality of nodes according to the size of the search area;
An expectation calculation step of calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile before communication with the lost mobile is lost. and,
an adjustment step of, after the flight, adjusting the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
a flight route generation step of selecting nodes based on the degree of expectation and generating a flight route using the selected nodes;
is characterized by executing

Also, in order to achieve the above purpose, the search system in one aspect includes:
the search device
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
selecting a node based on the expectation and generating a flight route using the selected node;
An unmanned aerial vehicle for searching for the lost mobile object,
Flying based on the flight route and receiving radio waves emitted from a transmitter provided on the lost mobile object,
measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
The search device is
After the flight, adjusting the degree of expectation set for each of the nodes based on the measured position and altitude and the strength of the received radio wave,
A node is selected based on the degree of expectation, and the selected node is used to generate the new flight route.

Further, to achieve the above objectives, in one aspect the search system includes:
the search device
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
selecting a node based on the expectation and generating a flight route using the selected node;
An unmanned aerial vehicle for searching for the lost mobile object,
Flying based on the flight route and receiving radio waves emitted from a transmitter provided on the lost mobile object,
measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
during flight, adjusting the expectations set for each of the nodes based on the measured position and altitude and the strength of the received radio waves;
A node is selected based on the degree of expectation, and the selected node is used to generate the new flight route.

As one aspect, a lost moving object can be quickly found.

FIG. 1 is a diagram for explaining an example of a search system according to Embodiment 1. FIG. FIG. 2 is a diagram for explaining an example of the search device of Embodiment 1. FIG. FIG. 3 is a diagram for explaining flight route setting. FIG. 4 is a diagram for explaining flight route setting. FIG. 5 is a diagram for explaining flight route setting. FIG. 6 is a diagram for explaining flight route setting. FIG. 7 is a diagram for explaining an example of an unmanned aerial vehicle according to Embodiment 1. FIG. FIG. 8 is a diagram for explaining an example of the operation of the search device according to the first embodiment; 9 is a diagram for explaining an example of the operation of the unmanned aerial vehicle according to the first embodiment; FIG. FIG. 10 is a diagram for explaining an example of a search system according to the second embodiment; FIG. 11 is a diagram for explaining an example of the operation of the search device according to the second embodiment; FIG. 12 is a diagram for explaining an example of the operation of the unmanned aerial vehicle according to the second embodiment; FIG. 13 is a diagram for explaining an example of a search system according to the third embodiment; FIG. 14 is a diagram for explaining an example of the operation of the search device according to the third embodiment; FIG. 15 is a diagram for explaining an example of the operation of the unmanned aerial vehicle according to the third embodiment; FIG. 16 is a diagram for explaining an example of a computer that implements the search device according to the first to third embodiments.

First, an overview will be given to facilitate understanding of the embodiments described below.
(1) If communication with the unmanned aerial vehicle is interrupted due to the radio wave conditions around the unmanned aerial vehicle, only the last position where communication with the unmanned aerial vehicle was possible is known.

(2) Depending on the model of the unmanned aerial vehicle, the operator may not be able to grasp the position information indicating the position where the unmanned aerial vehicle is flying. Therefore, if the unmanned aerial vehicle crashes in a position that cannot be visually observed, it is not known where the unmanned aerial vehicle crashed.

(3) If a GNSS (Global Navigation Satellite System) receiver is damaged when the unmanned aerial vehicle crashes, the position of the unmanned aerial vehicle cannot be estimated.

(4) Even if the GNSS receiver is not damaged, if the unmanned aerial vehicle crashes behind trees, mountains, etc., the positioning error increases, so it is not possible to know where the unmanned aerial vehicle crashed.

(5) Position estimation using three-point positioning based on distance conversion using the radio field intensity of the radio waves emitted from the lost unmanned aerial vehicle has a large estimation error.

Through the processes shown in (1) to (5), the inventor found the problem that the lost unmanned aerial vehicle could not be quickly searched by the method described above, and also solved the problem. I came to derive a means to do it.

That is, the inventor uses one or more unmanned aerial vehicles to search for the lost unmanned aerial vehicle, efficiently receives radio waves emitted from the lost unmanned aerial vehicle, and determines the lost This led to the derivation of a means to identify the crash position of the drone. As a result, the lost moving object can be quickly found.

Embodiments will be described below with reference to the drawings. In the drawings described below, elements having the same or corresponding functions are denoted by the same reference numerals, and repeated description thereof may be omitted.

(Embodiment 1)
The configuration of the search system according to Embodiment 1 will be described with reference to FIG. FIG. 1 is a diagram for explaining an example of a search system according to Embodiment 1. FIG.

[System configuration]
A search system 100 shown in FIG. 1 is a system for quickly searching for a lost mobile object 30 using a search device 10 and an unmanned aerial vehicle 20 . In the following description, for the sake of simplicity, the case where there is one unmanned aerial vehicle 20 will be described.

A search method of the search system 100 will be described. First, the search device 10 includes the lost position 31 at which communication with the lost mobile object 30 is lost, state information representing the state of the lost mobile object 30 acquired before communication with the lost mobile object 30 is lost, and A search area 32 (circular in the example of FIG. 1) is set based on.

Next, the search device 10 divides the search area 32 according to the size of the search area 32 and sets a plurality of nodes 33 (a plurality of rectangles in the example of FIG. 1).

Next, before starting the search, the search device 10 sets an initial Calculate the expected value (initial expected value).

The search device 10 then selects nodes based on the initial expectations and uses the selected nodes to generate a flight route for the unmanned aerial vehicle 20 . For example, a flight route is generated to fly through nodes with high expectations. Note that if there are a plurality of unmanned aerial vehicles 20, a flight route is generated for each of the unmanned aerial vehicles 20. FIG.

The unmanned aerial vehicle 20 then flies to collect data based on the flight route in order to search for the lost mobile object 30 . That is, the unmanned aerial vehicle 20 flies to receive radio waves emitted from a transmitter provided on the lost mobile object 30 . In addition, the unmanned aerial vehicle 20 measures the flying position and altitude.

Next, after the unmanned aerial vehicle 20 completes the data collection flight based on the flight route, the search device 10 detects the position and altitude measured by the unmanned aerial vehicle 20 and the strength of the received radio waves. When sufficient data to specify the position of is obtained, the unmanned aerial vehicle 20 is returned to the landing point.

In addition, when the number of nodes that can receive radio waves equal to or greater than the set radio field strength exceeds the threshold, and when the search for nodes around the node has been completed, it is determined that sufficient data has been collected. .

On the other hand, when the unmanned aerial vehicle 20 cannot acquire sufficient data to identify the position of the lost mobile object 30, the search device 10 sets the expectation set for each node 33 to the measured position and altitude. and the strength of the received radio wave.

The search device 10 then selects nodes based on the adjusted expectations and generates new flight routes using the selected nodes. Then, the unmanned aerial vehicle 20 is made to fly again on a new flight route for data collection.

In this way, data sufficient to identify the position of the lost moving object 30 can be efficiently collected, and the collected data can be used to represent the radio wave intensity status (for example, information that visualizes the radio wave intensity). ) can be generated, the lost moving object 30 can be quickly found based on the radio wave intensity situation.

[Device configuration]
The configuration of the search device in Embodiment 1 will be described.
FIG. 2 is a diagram for explaining an example of the search device of Embodiment 1. FIG. 3, 4, 5, and 6 are diagrams for explaining the setting of the flight route.

The search device 10 has a search area setting unit 11, a node setting unit 12, an expectation calculation unit 13, a flight route generation unit 14, an adjustment unit 15, an output information generation unit 16, and a communication unit 17. . The search device 10 is also connected to the output device 40 . The search device 10 may also have the ability to operate the unmanned aerial vehicle 20 .

The search device 10 is, for example, a CPU (Central Processing Unit), a programmable device such as an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), or one or more of them. Information processing devices such as circuits, server computers, personal computers, and mobile terminals.

The search area setting unit 11 is based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost. Set search area.

A lost mobile unit is a mobile unit that has become unable to communicate due to a failure, accident, or the like. The lost moving object has a transmitter. Mobile objects are, for example, unmanned aerial vehicles, self-driving vehicles, self-navigating ships, robots, and victim searching devices.

A transmitter is a device that emits radio waves with a constant intensity at regular intervals. Although the transmitter is mounted on the mobile body, it operates separately from the mobile body. The transmitter is, for example, a beacon device or the like.

The lost position is, for example, position coordinates based on GNSS. As for the lost position, if the mobile body has a function of acquiring position information through communication, the lost position is the position information immediately before communication became impossible.

Also, if the mobile body does not have a function of acquiring position information through communication, the lost position is obtained based on the situation in which the mobile body is lost (situation confirmed by visual observation). Alternatively, if a moving route is set for the moving object, the lost position may be obtained based on the set moving route.

The movement state information is information necessary for calculating the distance that the mobile body can move (movable distance). The moving state information includes, for example, the moving speed of the lost moving object, the remaining capacity of the battery mounted on the lost moving object, and the like.

For the movable distance, for example, the mobile body obtains the power consumption from the moving speed before communication becomes impossible, and the mobile body estimates the movable distance using the power consumption and the remaining battery capacity.

Specifically, as shown in FIG. 3 , the search area setting unit 11 sets a circular area having the lost item position 31 as the center point and the movable distance 34 as the radius as the search area 32 . Note that the search area is not limited to a circular shape.

The node setting unit 12 divides the search area according to the size of the search area and sets a plurality of nodes. Specifically, the node setting unit 12 divides the search area based on the division information (information including the shape of the node, parameters for determining the area of the node, etc.) associated with each area size of the search area. . In the example of FIG. 3 , the node setting unit 12 sets multiple nodes 33 .

Note that the division of nodes may be set based on the division information as well as the distance that radio waves transmitted by the transmitter reach.

The expectation level calculation unit 13 calculates an initial level of expectation to be set for each node before starting a search, based on the lost position and the moving direction of the lost mobile body before communication with the lost mobile body becomes impossible. .

If the moving object has a function of acquiring position information through communication, the direction of movement is obtained based on the position information before communication becomes impossible. In addition, if the mobile object does not have a function to acquire location information through communication, it may be based on the situation in which the mobile object was lost (situation confirmed by visual inspection), or the route set for the mobile object, or both. to find the direction of movement. In the example of FIG. 3 , the expectation calculation unit 13 sets the moving direction 35 .

The degree of expectation is information representing the probability that the lost moving object exists. The initial expectation is calculated based on the lost position and the moving direction before searching, and is set for each node. Note that the initially set expectation is, for example, a uniform distribution (1/N). N is the number of nodes in the search area 32;

Specifically, as shown in FIG. 4 , the expectation calculation unit 13 first estimates the moving direction 35 of the lost moving object 30 . Next, the degree-of-expectation calculator 13 sets a predetermined angle α with the loss position 31 as the vertex and the moving direction 35 as the center line.

Next, the expectation degree calculation unit 13 increases the degree of expectation of the nodes in the area determined by the predetermined angle α (high probability area in FIG. 4), lower expectations of nodes in low-lying areas). Expectations of nodes in other areas (probability areas in FIG. 4) are not changed. However, it is not limited to setting the degree of expectation described above.

The flight route generation unit 14 selects nodes based on the degree of expectation and generates a flight route that flies through the selected nodes. Specifically, the flight route generation unit 14 selects nodes for which the degree of expectation is higher than a preset threshold, and generates a flight route that flies through the selected nodes. Next, the flight route generator 14 sets a flight route for the unmanned aerial vehicle 20 .

The flight route is a route for automatically flying the unmanned aerial vehicle 20 used for searching. The flight route is, for example, information in which the order of flying the nodes is stored. It is desirable that the flight route is the shortest.

Moreover, it is desirable that the altitude at which the unmanned aerial vehicle 20 flies is constant. The reason is that the radio wave intensity changes with distance. Furthermore, it is desirable to set so that the same node can receive radio waves more than once. The reason is that by receiving radio waves at the same node a plurality of times, the measurement accuracy of the radio wave intensity at the node can be improved.

In the example of FIG. 4, the unmanned aerial vehicle 20 is located at a node ((6, 6) (5, 7) (6, 7) (4, 8) (5, 8) (3, 9) (4 , 9) (5,9) (2,10) (3,10) (4,10) (5,10) (3,11) (4,11) (5,11)). That is, it flies assuming that the actual position of the lost mobile object 30 exists in an area with a high probability.

However, as shown in FIG. 5, it is conceivable that the actual position of the lost moving object 30 does not exist in the high-probability area. In such a case, since sufficient data cannot be collected in one flight, a new flight route is generated for flying other than the already flown nodes, and the unmanned aerial vehicle 20 is flown again based on the new flight route.

After the search is started, the adjustment unit 15 adjusts the degree of expectation set for each node based on the position and altitude at which the unmanned aerial vehicle 20 for searching has flown and the intensity of the received radio wave.

Specifically, the adjustment unit 15 first acquires from the unmanned aerial vehicle 20 the flight position and altitude, and the radio wave intensity of the received radio wave. Next, the adjustment unit 15 changes the degree of expectation of the node based on the radio wave intensity.

For example, the adjusting unit 15 raises the expectations of the node that received the radio wave from the lost moving object 30 and the surrounding nodes. On the other hand, the adjustment unit 15 lowers the expectations of the node that did not receive the radio wave from the lost mobile object 30 and the nodes around it.

In the example of FIG. 5, since the node (3, 9) receives radio waves from the mobile object 30 that was lost in the first flight and is equal to or greater than the preset threshold, as shown in FIG. raise expectations of nodes (2,8) (3,8) (4,8) (2,9) (4,9) (2,10) (3,10) (4,10) around .

However, nodes other than the already flown node (3, 9) could not receive radio waves equal to or greater than the threshold, so the degree of expectation for the nodes other than the node (3, 9) is set low.

After that, the flight route generator 14 selects nodes based on the updated expectations and generates a new flight route using the selected nodes. The unmanned aerial vehicle 20 then flies based on the flight route.

In the example of FIG. 5, the unmanned aerial vehicle 20 is set to fly through nodes (2, 8), (3, 8), and (2, 9). The flight is repeated in this manner until sufficient data is collected. After that, when sufficient data to identify the position of the lost moving object 30 is obtained, the flight is terminated. On the other hand, when the unmanned aerial vehicle 20 cannot acquire sufficient data to identify the position of the lost mobile object 30, the expected degree set for each node 33 is calculated based on the measured position and altitude, and the received radio wave signal strength and

The output information generation unit 16 uses data collected by one or more unmanned aerial vehicles 20 to generate output information representing the state of radio wave intensity (for example, information that visualizes the radio wave intensity), and outputs the generated output information. Output to device 40 . The communication unit 17 communicates with a communication unit 25 of the unmanned aerial vehicle 20, which will be described later.

The output device 40 acquires output information (to be described later) that has been converted into a format that can be output by the output information generation unit 16, and outputs images, sounds, and the like generated based on the output information. The output device 40 is, for example, an image display device using liquid crystal, organic EL (Electro Luminescence), or CRT (Cathode Ray Tube). Furthermore, the image display device may include an audio output device such as a speaker. Note that the output device 40 may be a printing device such as a printer.

The configuration of the unmanned aerial vehicle in Embodiment 1 will be described.
FIG. 7 is a diagram for explaining an example of an unmanned aerial vehicle according to Embodiment 1. FIG.

The unmanned aerial vehicle 20 is an unmanned aerial vehicle for searching for the lost mobile object 30 . The unmanned aerial vehicle 20 has a receiver section 21 , a measurement section 22 , a control section 23 , a flight mechanism section 24 and a communication section 25 .

When the receiving unit 21 receives the radio wave transmitted from the transmitter provided in the lost moving object 30, the receiving unit 21 stores the radio wave intensity of the received radio wave in the storage unit. When an unmanned aerial vehicle for searching receives radio waves, the measurement unit 22 measures the position and altitude at which the radio waves are received.

When the control unit 23 sets a flight route for flying an area in which the lost mobile object is expected to exist in a preset search area, the control unit 23 flies the unmanned aerial vehicle 20 for searching. , controls the flight mechanism unit 24 .

The flight mechanism section 24 is a mechanism for causing the unmanned aerial vehicle 20 to fly. The communication unit 25 communicates with the communication unit 17 of the search device 10 .

The control unit 23 returns the unmanned aerial vehicle 20 to a preset landing point when the flight of the flight route is completed.

[Device operation]
Next, operations of the search device and the unmanned aerial vehicle in Embodiment 1 will be described with reference to FIGS. 8 and 9. FIG. FIG. 8 is a diagram for explaining an example of the operation of the search device according to the first embodiment; 9 is a diagram for explaining an example of the operation of the unmanned aerial vehicle according to the first embodiment; FIG. In the following description, the drawings will be referred to as appropriate. Also, in the first embodiment, the search method is implemented by operating the search device and the unmanned aerial vehicle. Therefore, the description of the search method in Embodiment 1 is replaced with the following description of the operation of the search device and the unmanned aerial vehicle.

The operation of the search device will be described with reference to FIG.
The search area setting unit 11 first stores the lost position at which communication with the lost mobile unit is lost, and the movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost. Based on this, a search area is set (step A1).

Specifically, in step A1, as shown in FIG. 3, the search area setting unit 11 sets, as the search area 32, a circular area whose center point is the lost position 31 and whose radius is the movable distance 34. . Note that the search area is not limited to a circular shape.

Next, the node setting unit 12 divides the search area according to the size of the search area and sets a plurality of nodes (step A2).

Specifically, in step A2, the node setting unit 12 divides the search area based on the division information (parameters for determining the shape of the node and the area of the node) associated with each area size of the search area. . In the example of FIG. 3 , the node setting unit 12 sets multiple nodes 33 .

Note that the division of nodes may be set based on the division information as well as the distance that radio waves transmitted by the transmitter reach.

Next, the expectation calculation unit 13 sets an initial expectation to each node based on the location of the lost mobile object and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible before the start of the search. is calculated (step A3).

Specifically, in step A3, the expectation calculation unit 13 first estimates the moving direction 35 of the lost moving object 30, as shown in FIG. Next, at step A3, the degree-of-expectation calculating unit 13 sets the predetermined angle α such that the movement direction 35 with the loss position 31 as the vertex is the center line.

Next, in step A3, the expectation degree calculation unit 13 increases the degree of expectation of the nodes in the area determined by the predetermined angle α (high-probability area in FIG. 4), Lower the expectation of nodes in the low-probability area in FIG. 4). Expectations of nodes in other areas (probability areas in FIG. 4) are not changed. However, it is not limited to setting the degree of expectation described above.

The flight route generator 14 selects nodes based on the degree of expectation, and generates a flight route that flies through the selected nodes (step A4). Specifically, in step A4, the flight route generation unit 14 selects nodes for which the degree of expectation is higher than a preset threshold, and generates a flight route that flies through the selected nodes.

Next, the flight route generator 14 sets a flight route for the unmanned aerial vehicle 20 (step A5). Then, the unmanned aerial vehicle 20 starts flying for data collection based on the flight route.

Next, when the flight along the set flight route is completed by the unmanned aerial vehicle 20 (step A6), the flight route generator 14 determines whether or not sufficient data for the search has been collected (step A7). Specifically, in step A7, after the unmanned aerial vehicle 20 completes the data collection flight based on the flight route, the flight route generation unit 14 calculates the position and altitude measured by the unmanned aerial vehicle 20 and the radio wave intensity of the received radio wave. can be acquired in an amount sufficient to identify the position of the lost moving object 30 (step A7: Yes), the flight is terminated and the process of step A9 is executed.

On the other hand, in step A7, if the unmanned aerial vehicle 20 cannot acquire sufficient data to specify the position of the lost mobile object 30 (step A7: No), the flight route generation unit 14 generates a new flight route. To generate it, first, the process of step A8 is executed.

The adjusting unit 15 adjusts the degree of expectation set for each node (step A8). Specifically, in step A<b>8 , the adjustment unit 15 first acquires the flight position and altitude and the radio wave intensity of the received radio wave from the unmanned aerial vehicle 20 . Next, in step A8, the adjusting unit 15 adjusts the degree of expectation set for each node based on the measured position and altitude and the radio wave intensity of the received radio wave.

For example, the adjusting unit 15 raises the expectations of the node that received the radio wave from the lost moving object 30 and the surrounding nodes. On the other hand, the adjustment unit 15 lowers the expectations of the node that did not receive the radio wave from the lost mobile object 30 and the nodes around it.

After that, in step A4, the flight route generation unit 14 selects nodes based on the updated expectations, generates a new flight route using the selected nodes, and in step A5 set.

The unmanned aerial vehicle 20 then flies again based on the flight route. Then, in step A6, the flight along the flight route set by the unmanned aerial vehicle 20 is completed. In this way, the processing of steps A4 to A8 is performed until sufficient data is collected for the search.

Next, when a sufficient amount of data to identify the position of the lost mobile object 30 is acquired, the output information generation unit 16 uses the data collected by one or more unmanned aerial vehicles 20 to determine the radio field intensity status. Output information (for example, information that visualizes radio wave intensity) is generated, and the generated output information is output to the output device 40 (step A9).

The operation of the unmanned aerial vehicle will be described with reference to FIG.
When the control unit 23 sets a flight route for flying an area in which the lost mobile object 30 is highly expected to exist in a preset search area (step B1), the unmanned aerial vehicle 20 for searching is set. to control the flight. The unmanned aerial vehicle 20 is flown based on the flight route.

Next, when the receiving unit 21 receives a radio wave transmitted from the transmitter provided on the lost mobile object 30 while the unmanned aerial vehicle 20 is in flight (step B2: Yes), the radio field intensity of the received radio wave, The position and altitude at which the radio waves are received are stored in the storage unit (step B3). In step B2, if the receiver 21 cannot receive the radio wave (step B2: No), the flight continues to receive the radio wave and collect data.

Next, when the flight of the flight route is completed (step B4: Yes), the control unit 23 causes the unmanned aerial vehicle 20 to return to the preset landing point (end of flight). On the other hand, if the flight of the flight route has not been completed (step B4: No), the control unit 23 shifts to the process of step B2 and continues the flight for data collection.

[Effect of Embodiment 1]
As described above, according to the first embodiment, sufficient data for specifying the position of the lost moving object 30 is efficiently collected, and information representing the radio wave intensity situation (for example, information that visualizes the radio wave intensity) is collected. Since it can be generated, the lost moving object 30 can be quickly found based on the radio wave intensity situation.

[program]
The search device program in Embodiment 1 may be a program that causes a computer to execute steps A1 to A9 shown in FIG. By installing this program in a computer and executing it, the search device and search method in Embodiment 1 can be realized. In this case, the computer processor functions as a search area setting unit 11, a node setting unit 12, an expectation calculation unit 13, a flight route generation unit 14, an adjustment unit 15, and an output information generation unit 16, and performs processing.

Also, the search device program in Embodiment 1 may be executed by a computer system constructed by a plurality of computers. In this case, for example, each computer functions as one of the search area setting unit 11, the node setting unit 12, the degree of expectation calculation unit 13, the flight route generation unit 14, the adjustment unit 15, and the output information generation unit 16. may

Also, the program for the unmanned aerial vehicle in the first embodiment may be any program that causes a computer mounted on the unmanned aerial vehicle to execute steps B1 to B4 shown in FIG. By installing this program on a computer and executing it, the search by the unmanned aerial vehicle in the first embodiment can be realized. In this case, the processor of the computer functions as a receiving section 21, a measuring section 22, a control section 23, and a flight mechanism section 24, and performs processing.

(Embodiment 2)
A search system according to the second embodiment will be described with reference to FIG.
FIG. 10 is a diagram for explaining an example of a search system according to the second embodiment; The difference between Embodiment 2 and Embodiment 1 is that the unmanned aerial vehicle generates a flight route in real time.

[System configuration]
A search system 200 of Embodiment 2 shown in FIG. 10 is a system for quickly searching for a lost mobile object 30 using a search device 10' and an unmanned aerial vehicle 20'. In the following explanation, for the sake of simplicity, the case where there is one unmanned aerial vehicle 20' will be explained.

First, the search device 10' includes the lost position at which communication with the lost mobile object 30 is lost, state information indicating the state of the lost mobile object 30 obtained before communication with the lost mobile object 30 is lost, Set the search area based on

Next, the search device 10' divides the search area according to the size of the search area and sets a plurality of nodes.

Next, before starting the search, the search device 10' sets initial values and Calculate the degree of expectation (initial degree of expectation).

Search device 10' then selects nodes based on the initial expectations and uses the selected nodes to generate a flight route for unmanned aerial vehicle 20'. For example, a flight route is generated to fly through nodes with high expectations. Note that if there are a plurality of unmanned aerial vehicles 20', a flight route is generated for each of the unmanned aerial vehicles 20'.

The unmanned aerial vehicle 20' then flies for data collection based on the flight route to search for the lost vehicle 30. FIG. That is, the unmanned aerial vehicle 20' flies to receive radio waves emitted from a transmitter provided on the lost mobile object 30. FIG. The unmanned aerial vehicle 20' also measures its flying position and altitude.

Next, when the unmanned aerial vehicle 20' receives radio waves transmitted from a transmitter provided on the lost moving body 30 during flight, the radio wave intensity of the received radio waves, the position and altitude at which the radio waves were received, and is transmitted to the search device 10' via the communication unit 25.

Next, the search device 10' adjusts the degree of expectation set for each node based on the strength of the radio wave received from the unmanned aerial vehicle 20' and the position and altitude at which the radio wave was received. Further, the search device 10' selects nodes based on expectations and generates new flight routes using the selected nodes.

Next, the search device 10 ′ transmits the generated new flight route to the unmanned aerial vehicle 20 ′ in flight via the communication unit 17 .

The unmanned aerial vehicle 20' then sets the new flight route received from the search device 10' and continues flying based on the set new flight route.

Next, when the search device 10 ′ acquires enough data to identify the position of the lost mobile object 30 from the position and altitude measured by the unmanned aerial vehicle 20 ′ and the radio wave intensity of the received radio wave. , causing the unmanned aerial vehicle 20' to terminate its flight.

Thus, in the second embodiment, since the flight route is generated in real time, it is not necessary to return and change the flight route as in the first embodiment. As a result, data sufficient for identifying the position of the lost moving object 30 can be collected more quickly than in the first embodiment.

[Device configuration]
The configuration of the search device in Embodiment 2 will be described.
As shown in FIG. 10, the search device 10' includes a search area setting unit 11, a node setting unit 12, an expectation calculation unit 13, a flight route generation unit 14', an adjustment unit 15', and an output information generation unit. It has a unit 16 and a communication unit 17 . The search device 10 ′ is also connected to an output device 40 .

Since the search area setting unit 11, the node setting unit 12, the degree of expectation calculation unit 13, the output information generation unit 16, and the communication unit 17 have already been described in the first embodiment, descriptions thereof will be omitted.

The adjustment unit 15' adjusts the degree of expectation set for each node based on the strength of the radio wave received from the unmanned aerial vehicle 20' in flight and the position and altitude at which the radio wave was received. After that, the flight route generator 14' generates a new flight route based on the adjusted expectations. Next, the flight route generation unit 14 ′ transmits the generated new flight route to the unmanned aerial vehicle 20 ′ in flight via the communication unit 17 .

The configuration of the unmanned aerial vehicle in Embodiment 2 will be described.
The unmanned aerial vehicle 20' has a receiving section 21, a measuring section 22, a control section 23', a flight mechanism section 24, and a communication section 25, as shown in FIG.

Since the reception unit 21, the measurement unit 22, the flight mechanism unit 24, and the communication unit 25 have already been described in the first embodiment, descriptions thereof will be omitted.

The control unit 23' sets the new flight route received from the search device 10' and continues the data collection flight. Further, when sufficient data to identify the position of the lost mobile object 30 is acquired (when the search device 10' notifies the completion of the flight), the control unit 23' sets the unmanned aircraft 20' to the landing point. control to return to

[Device operation]
Next, operations of the search device and the unmanned aerial vehicle in Embodiment 2 will be described with reference to FIGS. 11 and 12. FIG. FIG. 11 is a diagram for explaining an example of the operation of the search device according to the second embodiment; FIG. 12 is a diagram for explaining an example of the operation of the unmanned aerial vehicle according to the second embodiment; In the following description, the drawings will be referred to as appropriate. Also, in the second embodiment, the search method is implemented by operating the search device and the unmanned aerial vehicle. Therefore, the description of the search method in the second embodiment is replaced with the following description of the operation of the search device and the unmanned aerial vehicle.

The operation of the search device will be described with reference to FIG.
Since the processes of steps A1 to A5 and A7 to A9 in FIG. 11 have already been described, detailed description of these processes will be omitted.

When the unmanned aerial vehicle 20 ′ receives radio waves from the lost moving object 30 while flying based on the flight route, it sends data (the intensity of the received radio waves) to the search device 10 ′ via the communication unit 25 . and the position and altitude at which the radio wave was received).

If the search device 10' has received the data (step C1: Yes), the flight route generator 14 determines whether or not sufficient data for the search has been collected (step A7).

If sufficient data for the search has been collected (step A7: Yes), the search device 10' causes the unmanned aerial vehicle 20' to terminate the flight, and executes the processing of step A9.

If the data sufficient for the search has not been collected (step A7: No), the adjustment unit 15' sets each node based on the radio wave intensity of the received radio wave and the position and altitude at which the radio wave was received. Adjust the degree of expectation (step A8).

Next, the flight route generator 14' generates a new flight route based on the adjusted expectations (step A4'). Next, the flight route generation unit 14' transmits the generated new flight route to the unmanned aerial vehicle 20' in flight via the communication unit 17 (step C2).

If the search device 10' cannot receive data for a preset time (step C1: No), the currently set flight route is flown back to the landing point.

The operation of the unmanned aerial vehicle will be described with reference to FIG.
Since the processing of steps B1 to B4 in FIG. 12 has already been described, detailed description of these processing will be omitted.

The radio field strength of the radio wave received by the unmanned aerial vehicle 20' and the position and altitude at which the radio wave was received are stored in the storage unit (step B3). Data (radio field intensity of the received radio wave, position and altitude at which the radio wave was received) is transmitted (step D1).

Next, when a new flight route generated based on the transmitted data is received from the search device 10' (step D2: Yes), the control section 23' sets a new flight route (step D3).

If the radio wave cannot be received (step B2: No), the flight continues to receive the radio wave and collect data. If a new flight route cannot be received from the search device 10' (step D2: No), the flight continues to receive radio waves and collect data.

Next, when the flight along the flight route is completed (step B4: Yes), the control unit 23' causes the unmanned aerial vehicle 20 to return to the preset landing point (end of flight). On the other hand, if the flight of the flight route has not been completed (step B4: No), the control unit 23' proceeds to the process of step B2 and continues the flight for data collection.

[Effect of Embodiment 2]
As described above, according to the second embodiment, since the flight route is generated in real time, it is not necessary to return and change the flight route as in the first embodiment. As a result, data sufficient for identifying the position of the lost moving object 30 can be collected more quickly than in the first embodiment.

[program]
The search device program in the second embodiment may be any program that causes a computer to execute steps A1 to A9, C1, and C2 shown in FIG. By installing this program in a computer and executing it, the search device and search method in Embodiment 2 can be realized. In this case, the processor of the computer functions as a search area setting unit 11, a node setting unit 12, an expectation calculation unit 13, a flight route generation unit 14', an adjustment unit 15', and an output information generation unit 16, and performs processing.

Also, the search device program in Embodiment 1 may be executed by a computer system constructed by a plurality of computers. In this case, for example, each computer serves as one of the search area setting unit 11, the node setting unit 12, the degree of expectation calculation unit 13, the flight route generation unit 14', the adjustment unit 15', and the output information generation unit 16. may function.

Also, the program for the unmanned aerial vehicle in the second embodiment may be any program that causes a computer mounted on the unmanned aerial vehicle to execute steps B1 to B4 and D1 to D3 shown in FIG. By installing this program on a computer and executing it, the search by the unmanned aerial vehicle in the second embodiment can be realized. In this case, the processor of the computer functions as a receiving section 21, a measuring section 22, a control section 23', and a flight mechanism section 24 to perform processing.

(Embodiment 3)
A search system according to the third embodiment will be described with reference to FIG.
FIG. 13 is a diagram for explaining an example of a search system according to the third embodiment; The difference between the third embodiment and the first embodiment is that the unmanned aerial vehicle generates a flight route in real time, as in the second embodiment.

Furthermore, in Embodiment 3, unlike Embodiment 2, the unmanned aerial vehicle generates and sets a flight route.

[System configuration]
A search system 300 of Embodiment 3 shown in FIG. 13 is a system for quickly searching for a lost mobile object 30 using a search device 10″ and an unmanned aerial vehicle 20″. In the following description, for the sake of simplicity, a single unmanned aerial vehicle 20″ will be used, but in practice, multiple unmanned aerial vehicles 20″ may be used for searching.

First, the search device 10″ includes the lost position at which communication with the lost mobile object 30 is lost, state information representing the state of the lost mobile object 30 obtained before communication with the lost mobile object 30 is lost, Set the search area based on

Next, the search device 10″ divides the search area according to the size of the search area and sets a plurality of nodes.

Next, before starting the search, the search device 10'' sets initial values and Calculate the degree of expectation (initial degree of expectation).

The search device 10'' then selects nodes based on the initial expectations and uses the selected nodes to generate a flight route for the unmanned aerial vehicle 20''. For example, a flight route is generated to fly through nodes with high expectations. If there are a plurality of unmanned aerial vehicles 20'', a flight route is generated for each of the unmanned aerial vehicles 20'.

Next, the search device 10″ sets flight routes and node information (information representing nodes and expectations set for each node) to the unmanned aerial vehicle 20″.

Next, the unmanned aerial vehicle 20″ flies to collect data based on the flight route in order to search for the lost mobile object 30. fly to receive the radio waves emitted by the transmitter. The unmanned aerial vehicle 20″ also measures its position and altitude as it flies.

Next, when the unmanned aerial vehicle 20″ receives radio waves transmitted from a transmitter provided on the lost mobile object 30 during flight, the radio wave intensity of the received radio waves, the position and altitude at which the radio waves were received, and is transmitted to the search device 10″ through the communication unit 25.

Also, the unmanned aerial vehicle 20″ adjusts the degree of expectation set for each node based on the radio wave intensity and the position and altitude at which the radio wave was received.

Additionally, the unmanned aerial vehicle 20″ selects nodes based on expectations and generates new flight routes using the selected nodes.

The unmanned aerial vehicle 20″ then sets a new flight route and continues flying based on the set new flight route.

Next, when the search device 10 ″ acquires enough data to identify the position of the lost mobile object 30 from the position and altitude measured by the unmanned aerial vehicle 20 ″ and the radio wave intensity of the received radio wave, , causing the unmanned aerial vehicle 20″ to terminate its flight.

As described above, since the flight route is generated in real time in the third embodiment, it is not necessary to return and change the flight route as in the first embodiment. As a result, data sufficient for identifying the position of the lost moving object 30 can be collected more quickly than in the first embodiment.

[Device configuration]
The configuration of the search device in Embodiment 3 will be described.
As shown in FIG. 13, the search device 10″ includes a search area setting unit 11, a node setting unit 12, an expectation calculation unit 13, a flight route generation unit 14, an output information generation unit 16, and a communication unit 17. The search device 10 ″ is also connected to an output device 40 .

Since the search area setting unit 11, the node setting unit 12, the degree of expectation calculation unit 13, the flight route generation unit 14, the output information generation unit 16, and the communication unit 17 have already been described in the first embodiment, the description of these will be omitted. omitted.

The configuration of the unmanned aerial vehicle in Embodiment 3 will be described.
As shown in FIG. 13, the unmanned aerial vehicle 20″ includes a receiving unit 21, a measuring unit 22, a control unit 23″, a flight mechanism unit 24, a communication unit 25, a flight route generating unit 14″, and an adjusting unit. 15″.

Since the reception unit 21, the measurement unit 22, the flight mechanism unit 24, and the communication unit 25 have already been described in the first embodiment, descriptions thereof will be omitted.

The adjustment unit 15″ adjusts the degree of expectation set for each node based on the strength of the radio waves received by the unmanned aerial vehicle 20″ in flight and the position and altitude at which the radio waves are received. After that, the flight route generator 14″ generates a new flight route based on the adjusted expectations.

The control unit 23″ sets a new flight route and continues the data collection flight. Further, when sufficient data to identify the position of the lost moving object 30 is acquired (from the search device 10″ When the flight completion is notified), the control unit 23'' performs control to return the unmanned aerial vehicle 20'' to the landing point.

[Device operation]
Next, operations of the search device and the unmanned aerial vehicle in Embodiment 3 will be described with reference to FIGS. 14 and 15. FIG. FIG. 14 is a diagram for explaining an example of the operation of the search device according to the third embodiment; FIG. 15 is a diagram for explaining an example of the operation of the unmanned aerial vehicle according to the third embodiment; In the following description, the drawings will be referred to as appropriate. Further, in Embodiment 3, the search method is implemented by operating the search device and the unmanned aerial vehicle. Therefore, the description of the search method in the third embodiment is replaced with the following description of the operation of the search device and the unmanned aerial vehicle.

The operation of the search device will be described with reference to FIG.
Since the processing of steps A1 to A5, A7, A9, and C1 in FIG. 14 has already been described, detailed description of these processing will be omitted.

If the search device 10″ cannot receive data for a preset time (step C1: No), the currently set flight route is flown back to the landing point.

The operation of the unmanned aerial vehicle will be described with reference to FIG.
Since the processes of steps B1 to B4, D1, and D3 in FIG. 15 have already been described, detailed description of these processes will be omitted.

When the unmanned aerial vehicle 20″ receives a radio wave transmitted from the transmitter provided on the lost moving object 30 during flight (step B2: Yes), the radio wave intensity of the received radio wave and the position at which the radio wave was received and altitude are transmitted to the search device 10″ through the communication unit 25 (step D1).

Next, the adjuster 15″ adjusts the degree of expectation set for each node based on the radio wave intensity and the position and altitude at which the radio wave was received (step E1).

Further, the flight route generator 14'' selects a node based on the degree of expectation and generates a new flight route using the selected node (step E2). A route is set (step D3).

If the radio wave cannot be received (step B2: No), the flight continues to receive the radio wave and collect data.

Next, when the flight along the flight route is completed (step B4: Yes), the control unit 23' causes the unmanned aerial vehicle 20 to return to the preset landing point (end of flight). On the other hand, if the flight of the flight route has not been completed (step B4: No), the control unit 23' proceeds to the process of step B2 and continues the flight for data collection.

[Effect of Embodiment 3]
As described above, according to the third embodiment, since the flight route is generated in real time, it is not necessary to return and change the flight route as in the first embodiment. As a result, data sufficient for identifying the position of the lost moving object 30 can be collected more quickly than in the first embodiment.

[program]
The search device program in the third embodiment may be any program that causes a computer to execute steps A1 to A5, A7, A9, and C1 shown in FIG. By installing this program in a computer and executing it, the search device and search method in Embodiment 3 can be realized. In this case, the computer processor functions as a search area setting unit 11, a node setting unit 12, an expectation calculation unit 13, a flight route generation unit 14, and an output information generation unit 16, and performs processing.

Also, the search device program in Embodiment 3 may be executed by a computer system constructed by a plurality of computers. In this case, for example, each computer may function as one of the search area setting unit 11, the node setting unit 12, the degree of expectation calculation unit 13, the flight route generation unit 14, and the output information generation unit 16, respectively.

Also, the program for the unmanned aerial vehicle in the third embodiment may be any program that causes a computer mounted on the unmanned aerial vehicle to execute steps B1 to B4, D1, D3, E1, and E2 shown in FIG. By installing this program in a computer and executing it, the search by the unmanned aerial vehicle in Embodiment 3 can be realized. In this case, the processor of the computer functions as a receiving section 21, a measuring section 22, a control section 23'', a flight mechanism section 24, an adjusting section 15'', and a flight route generating section 14'', and performs processing.

[Physical configuration]
Here, a computer that implements the search device by executing the programs in Embodiments 1 to 3 will be described with reference to FIG. FIG. 16 is a diagram for explaining an example of a computer that implements the search device according to the first to third embodiments.

As shown in FIG. 16, a computer 110 includes a CPU (Central Processing Unit) 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader/writer 116, and a communication interface 117. and These units are connected to each other via a bus 121 so as to be able to communicate with each other. The computer 110 may include a GPU (Graphics Processing Unit) or an FPGA (Field-Programmable Gate Array) in addition to the CPU 111 or instead of the CPU 111 .

The CPU 111 expands the programs (codes) in the present embodiment stored in the storage device 113 into the main memory 112 and executes them in a predetermined order to perform various calculations. The main memory 112 is typically a volatile storage device such as a DRAM (Dynamic Random Access Memory). Also, the program in this embodiment is provided in a state stored in a computer-readable recording medium 120 . Note that the program in this embodiment may be distributed on the Internet connected via the communication interface 117 . Note that the recording medium 120 is a non-volatile recording medium.

Further, as a specific example of the storage device 113, in addition to a hard disk drive, a semiconductor storage device such as a flash memory can be mentioned. Input interface 114 mediates data transmission between CPU 111 and input devices 118 such as a keyboard and mouse. The display controller 115 is connected to the display device 119 and controls display on the display device 119 .

Data reader/writer 116 mediates data transmission between CPU 111 and recording medium 120 , reads programs from recording medium 120 , and writes processing results in computer 110 to recording medium 120 . Communication interface 117 mediates data transmission between CPU 111 and other computers.

Specific examples of the recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital); magnetic recording media such as flexible disks; An optical recording medium such as a ROM (Compact Disk Read Only Memory) can be mentioned.

Note that the search device in the embodiment can also be realized by using hardware corresponding to each part instead of a computer in which a program is installed. Furthermore, the search device may be partly implemented by a program and the rest by hardware.

[Appendix]
The following additional remarks are disclosed regarding the above embodiments. Some or all of the embodiments described above can be expressed by the following (Appendix 1) to (Appendix 10), but are not limited to the following description.

(Appendix 1)
An unmanned aerial vehicle for searching lost mobile objects,
a receiving unit that receives radio waves transmitted from a transmitter provided in the lost moving object;
a measuring unit that measures the position and altitude at which the unmanned aerial vehicle for searching is flying;
a control unit that controls the flight of the unmanned aerial vehicle for searching in a preset search area using a flight route for flying in an area where the lost mobile object is highly expected to exist;
An unmanned aerial vehicle for searching with

(Appendix 2)
The unmanned aerial vehicle for searching of Clause 1, comprising:
The search area is determined based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost. Set up an unmanned aerial vehicle for searching.

(Appendix 3)
The unmanned aerial vehicle for searching according to Appendix 2,
The degree of expectation is set for each node divided according to the area of the search area,
The expectation degree, which is the initial value set for each of the nodes, is calculated based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object was lost. unmanned aerial vehicle.

(Appendix 4)
The unmanned aerial vehicle for searching according to Appendix 3,
an adjustment unit that adjusts the degree of expectation set for each of the nodes after flight based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio waves. unmanned aerial vehicle for

(Appendix 5)
An unmanned aerial vehicle for searching according to any one of Appendices 1 to 4,
An unmanned aerial vehicle for searching, comprising: a flight route generator, wherein the flight route is generated by selecting nodes based on the expectation and using the selected nodes.

(Appendix 6)
setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; a search area setting unit;
a node setting unit that sets a plurality of nodes by dividing the search area according to the size of the search area;
An expectation calculation unit that calculates an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile before communication with the lost mobile is lost. and,
an adjustment unit that, after flight, adjusts the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
a flight route generation unit that selects a node based on the degree of expectation and generates a flight route using the selected node;
search device with

(Appendix 7)
the computer
setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; a search area setting step;
a node setting step of dividing the search area and setting a plurality of nodes according to the size of the search area;
An expectation calculation step of calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile before communication with the lost mobile is lost. and,
an adjustment step of, after the flight, adjusting the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
a flight route generation step of selecting nodes based on the degree of expectation and generating a flight route using the selected nodes;
Search method to perform.

(Appendix 8)
to the computer,
setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; a search area setting step;
a node setting step of dividing the search area and setting a plurality of nodes according to the size of the search area;
An expectation calculation step of calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile before communication with the lost mobile is lost. and,
an adjustment step of, after the flight, adjusting the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
a flight route generation step of selecting nodes based on the degree of expectation and generating a flight route using the selected nodes;
A program containing instructions that causes a

(Appendix 9)
the search device
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
selecting a node based on the expectation and generating a flight route using the selected node;
An unmanned aerial vehicle for searching for the lost mobile object,
Flying based on the flight route and receiving radio waves emitted from a transmitter provided on the lost mobile object,
measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
The search device is
After the flight, adjusting the degree of expectation set for each of the nodes based on the measured position and altitude and the strength of the received radio wave,
A search system that selects nodes based on the expectations and generates the new flight route using the selected nodes.

(Appendix 10)
the search device
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
selecting a node based on the expectation and generating a flight route using the selected node;
An unmanned aerial vehicle for searching for the lost mobile object,
Flying based on the flight route and receiving radio waves emitted from a transmitter provided on the lost mobile object,
measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
during flight, adjusting the expectations set for each of the nodes based on the measured position and altitude and the strength of the received radio waves;
A search system that selects nodes based on the expectations and generates the new flight route using the selected nodes.

Although the present invention has been described with reference to the embodiments, the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

As described above, according to the present invention, a lost moving object can be quickly found. INDUSTRIAL APPLICABILITY The present invention is useful in the field of searching for lost moving bodies.

10 search device 11 search area setting unit 12 node setting unit 13 expectation calculation unit 14, 14', 14'' flight route generation unit 15, 15', 15'' adjustment unit 16 output information generation unit 17 communication unit 20 unmanned aerial vehicle 21 reception Unit 22 Measurement Unit 23, 23′ Control Unit 24 Flight Mechanism Unit 25 Communication Unit 30 Moving Body 40 Output Devices 100, 200, 300 Search System 110 Computer 111 CPU
112 Main memory 113 Storage device 114 Input interface 115 Display controller 116 Data reader/writer 117 Communication interface 118 Input device 119 Display device 120 Recording medium 121 Bus

Claims (10)

An unmanned aerial vehicle for searching lost mobile objects,
receiving means for receiving radio waves transmitted from a transmitter provided in the lost mobile body;
measuring means for measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
a control means for controlling the flight of the unmanned aerial vehicle for searching in a preset search area using a flight route for flying in an area where the lost mobile object is highly expected to exist;
An unmanned aerial vehicle for searching with An unmanned aerial vehicle for searching according to claim 1,
The search area is determined based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost. Set up an unmanned aerial vehicle for searching. An unmanned aerial vehicle for searching according to claim 2,
The degree of expectation is set for each node divided according to the area of the search area,
The expectation degree, which is the initial value set for each of the nodes, is calculated based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object was lost. unmanned aerial vehicle. An unmanned aerial vehicle for searching according to claim 3,
adjusting means for adjusting, after flight, the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio waves. unmanned aerial vehicle for An unmanned aerial vehicle for searching according to any one of claims 1 to 4,
An unmanned aerial vehicle for searching, comprising: flight route generation means for selecting nodes based on the expectation and generating the flight route using the selected nodes. setting a search area based on the lost position at which communication with the lost mobile object is lost and movement state information representing the state of the lost mobile object obtained before communication with the lost mobile object is lost; search area setting means;
node setting means for setting a plurality of nodes by dividing the search area according to the size of the search area;
Expectation level calculation means for calculating an expectation level as an initial value to be set for each of the nodes based on the lost position and the direction of movement of the lost mobile body before communication with the lost mobile body becomes impossible. and,
adjusting means for adjusting, after the flight, the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave;
flight route generating means for selecting nodes based on the degree of expectation and generating a flight route using the selected nodes;
search device with the computer
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
After the flight, adjusting the degree of expectation set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio wave,
A search method that selects nodes based on the expectations and generates a flight route using the selected nodes. to the computer,
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information representing the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile body before communication with the lost mobile body becomes impossible;
After the flight, adjusting the expectations set for each of the nodes based on the position and altitude at which the unmanned aerial vehicle for searching flew and the strength of the received radio waves,
A program comprising instructions for: selecting a node based on the degree of expectation; and generating a flight route using the selected node. the search device
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
selecting a node based on the expectation and generating a flight route using the selected node;
An unmanned aerial vehicle for searching for the lost mobile object,
Flying based on the flight route and receiving radio waves emitted from a transmitter provided on the lost mobile object,
measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
The search device is
After the flight, adjusting the degree of expectation set for each of the nodes based on the measured position and altitude and the strength of the received radio wave,
A search system that selects nodes based on the expectations and generates the new flight route using the selected nodes. the search device
setting a search area based on the lost position at which communication with the lost mobile unit is lost and movement state information indicating the state of the lost mobile unit obtained before communication with the lost mobile unit is lost;
setting a plurality of nodes by dividing the search area according to the area of the search area;
calculating an expectation as an initial value to be set for each of the nodes based on the lost position and the moving direction of the lost mobile object before communication with the lost mobile object becomes impossible;
selecting a node based on the expectation and generating a flight route using the selected node;
An unmanned aerial vehicle for searching for the lost mobile object,
Flying based on the flight route and receiving radio waves emitted from a transmitter provided on the lost mobile object,
measuring the position and altitude at which the unmanned aerial vehicle for searching is flying;
during flight, adjusting the expectations set for each of the nodes based on the measured position and altitude and the strength of the received radio waves;
A search system that selects nodes based on the expectations and generates the new flight route using the selected nodes.

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