JP2019191888A - Unmanned flying object, unmanned flying method and unmanned flying program - Google Patents

Abstract

To provide an unmanned flying object, an unmanned flying method, and an unmanned flying program that ensures flying while reducing the influence of environmental conditions and determining a current position.SOLUTION: The unmanned flying object 1 that is thrust by the rotation of a propeller includes positioning means that calculates a positioning position by using a positioning radio wave from a navigation satellite, position estimation means that calculates an estimated position by estimating a current position by plural types of position estimation methods that do not use the positioning radio wave, and positioning means that determines the current position by performing weighting at the positioning position and/or the estimated position.SELECTED DRAWING: Figure 6

Description

  The present invention relates to an unmanned air vehicle, an unmanned flight method, and an unmanned flight program.

  Conventionally, small unmanned aerial vehicles (also called “drones”) are used for inspection of infrastructure such as bridges. In order to fly a predetermined route while maintaining a predetermined distance from a target such as a bridge, it is necessary to measure the position of the drone. The position of the drone can be measured by receiving a positioning radio wave from a navigation satellite such as a GPS satellite (Global Positioning System) or by using a distance sensor such as an ultrasonic distance sensor (for example, Patent Document 1).

Japanese Patent Laying-Open No. 2015-217785

  By the way, it is sometimes difficult to measure the position of the drone in the field of infrastructure inspection or the like depending on the environmental conditions. For example, there are cases where positioning radio waves cannot be received from the number of navigation satellites necessary for positioning. In the case of an ultrasonic distance sensor, it is difficult to accurately measure the distance depending on the surface shape of the object.

  The present invention is an attempt to solve such a problem, and provides an unmanned air vehicle, an unmanned flight method, and an unmanned flight program capable of flying while reducing the influence of environmental conditions and determining the current position. With the goal.

  A first invention is an unmanned air vehicle that obtains thrust by rotation of a propeller, positioning means that measures a current position by using a positioning radio wave from a navigation satellite and calculates a positioning position; and the positioning radio wave In position estimation means for calculating an estimated position by estimating a current position by a plurality of types of position estimation methods that do not use the positioning position and the estimated position, or in the estimated position estimated by a plurality of types of the position estimation methods An unmanned aerial vehicle having position determining means for performing weighting and determining a current position.

  According to the configuration of the first invention, the unmanned aerial vehicle determines the current position by weighting the positioning position and the estimated position obtained by estimating the current position using a plurality of types of position estimation methods. Even if this position calculation (estimation) method does not function under a specific environmental condition, the current position can be determined using the positioning position or the estimated position obtained by another position calculation (estimation) method. For this reason, the unmanned air vehicle can fly while reducing the influence of environmental conditions and determining the current position.

  According to a second invention, in the configuration of the first invention, the position estimation means estimates a current position based on an output of an inertial sensor and calculates a first estimated position; three-dimensional data; Second estimating means for calculating a second estimated position by estimating a current position based on photographing data obtained by photographing with a camera, and estimating a current position based on the three-dimensional data and the output of the laser scanner. An unmanned aerial vehicle including at least one of third estimation means for calculating three estimated positions.

  According to a third invention, in the configuration of the second invention, the position determining means does not use the positioning position when the number of the navigation satellites capable of receiving the positioning radio waves is less than a predetermined number, An unmanned aerial vehicle configured to determine a current position based on the estimated position.

  According to a fourth aspect of the present invention, in the configuration of the second aspect of the invention or the third aspect of the invention, the position determining means is the estimated position estimated immediately before any of the estimated positions estimated in the plurality of types of position estimation methods. And an unmanned aerial vehicle configured not to use the estimated position exceeding the allowable range when there is a difference exceeding the allowable range.

  According to a fifth aspect of the present invention, in any one of the first to fourth aspects, the position determining means is configured to perform the weighting based on an output of an inertial sensor. It is.

  A sixth invention is a positioning step in which an unmanned air vehicle that obtains thrust by rotating a propeller measures a current position by using a positioning radio wave from a navigation satellite to calculate a positioning position, and uses the positioning radio wave. A position estimation step of estimating the current position by a plurality of types of position estimation methods and calculating an estimated position, and weighting in the positioning position and the estimated position, or the estimated position estimated by a plurality of types of position estimation methods And an unmanned flight method for performing a position determination step to determine a current position.

  The seventh invention is a positioning means for calculating a positioning position by positioning a current position using a positioning radio wave from a navigation satellite, a computer that controls an unmanned air vehicle that obtains thrust by rotation of a propeller, the positioning In the position estimation means for estimating the current position by a plurality of types of position estimation methods that do not use radio waves and calculating the estimated position, the positioning position and the estimated position, or the estimated position estimated by a plurality of types of the position estimation methods It is an unmanned flight program for functioning as position determining means for determining the current position by performing weighting.

  According to the present invention, it is possible to fly while determining the current position while reducing the influence of environmental conditions.

It is the schematic which shows the effect | action of the unmanned air vehicle which concerns on embodiment of this invention. It is the schematic which shows the unmanned air vehicle which concerns on embodiment of this invention. It is the schematic which shows the function structure of an unmanned air vehicle. It is a conceptual diagram which shows the method of weighting. It is the schematic which shows operation | movement of an unmanned air vehicle. It is a flowchart which shows a motion of an unmanned air vehicle.

  Hereinafter, modes for carrying out the present invention (hereinafter referred to as embodiments) will be described in detail. In the following description, the same reference numerals are given to the same components, and the description thereof is omitted or simplified. Note that description of configurations that can be appropriately implemented by those skilled in the art will be omitted, and only the basic configuration of the present invention will be described.

  The drone 1 shown in FIG. 1 obtains thrust by the rotation of a propeller and autonomously flies along a predetermined route. The drone 1 is an example of an unmanned air vehicle. The drone 1 is an unmanned air vehicle flying in the air. The drone 1 starts work in response to an instruction from the base station 50 (see FIG. 3) that manages the drone 1, and performs charging and the like in the base station 50.

  The drone 1 inspects the bottom surface 200a of the highway 200 and the piers 202A, 202B, and 202C while autonomously flying. In this specification, the space including the bottom surface 200a of the highway 200 and the piers 202A, 202B, and 202C is an example of a flight region.

  The drone 1 receives positioning radio waves from the navigation satellites 300A, 300B, 300C, and 300D, and measures the current position. The current position measured using the positioning radio wave is defined as a positioning position A. The positioning position A is an example of a positioning position.

  The drone 1 can receive positioning radio waves when there is no obstacle between the navigation satellite 300A and the like, such as the position P1 above the highway 200, for example. However, when the drone 1 is located at a position where the positioning radio wave cannot be received (for example, position P2), for example, an obstacle such as the highway 200 exists between the drone 1 and the navigation satellite 300A. The drone 1 cannot receive positioning radio waves. In this case, the drone 1 estimates the current position using other types of position estimation methods. As a position estimation method, for example, a method using an output from an inertial sensor, a method using a pre-stored three-dimensional map and photographing data obtained by photographing with a camera, and a three-dimensional map and an output of a laser scanner are used. There is a method to use. The current position estimated using the output from the inertial sensor is the estimated position B, the current position estimated with reference to the captured data obtained by photographing with the camera and the three-dimensional map, the estimated position C, and the output of the laser scanner The current position is set as the estimated position D with reference to the three-dimensional map. The estimated position B is an example of a first estimated position, the estimated position C is an example of a second estimated position, and the estimated position D is an example of a third estimated position. A three-dimensional map is an example of three-dimensional data.

  The drone 1 is inspected at a position separated from the bottom surface 200a, the pier 202A, and the like by a predetermined distance on a predetermined route. In order to maintain the distance from the bottom surface 200a and the like, the drone 1 Use a 3D map of the current location and flight region. The three-dimensional map is generated separately in the drone 1 and stored in the inspection site while maintaining the distance from the target based on the current position of the drone 1 and the three-dimensional map. At this time, the drone 1 weights the positioning position A and the estimated positions BD to determine the current position.

  As shown in FIG. 2, the drone 1 has a housing 2. The housing 2 receives positioning radio waves from a navigation satellite system such as a computer that controls each part of the drone 1, an autonomous flight device, a wireless communication device, an inertial sensor 20 (Internal Measurement Unit), and a GPS (Global Positioning System). An antenna 22 for receiving, an atmospheric pressure sensor, a battery and the like are arranged. A laser scanner (not shown) is disposed on the lower surface of the housing 20 (the surface opposite to the side where the antenna 22 is disposed). In addition, a camera 14 is disposed in the housing 2 via a fixing device 12. The camera 14 inspects bridges and the like. The camera 14 is a visible light camera or a near-infrared camera, but may be a switchable hybrid camera. The camera 14 is an example of an information collecting unit. The fixing device 12 is a three-axis fixing device (so-called gimbal) that can minimize blurring of an image captured by the camera 14 and can control the optical axis of the camera 14 in an arbitrary direction.

  A round bar-like arm 4 is connected to the housing 2. A motor 6 is connected to each arm 4, and a propeller 8 is connected to each motor 6. Each motor 6 is a direct current motor (brushless DC motor). Each motor 6 is independently controlled by the autonomous flight device in the housing 2 so that the drone 1 can freely move in the vertical and horizontal directions, stop in the air (hovering), and control the attitude. It has become.

  A protective frame 10 is connected to the arm 4 to prevent the propeller 8 from coming into direct contact with an external object. The arm 4 and the protective frame 10 are made of, for example, carbon fiber reinforced plastic, and are lightweight while maintaining strength.

  FIG. 3 is a diagram illustrating a functional configuration of the drone 1. As shown in FIG. 3, the drone 1 includes a CPU (Central Processing Unit) 100, a storage unit 102, a wireless communication unit 104, a satellite positioning unit 106, an inertial sensor unit 108, a laser scanner unit 110, a drive control unit 112, an image. A processing unit 114 and a power supply unit 120 are included.

  The drone 1 can communicate with the base station 50 by the wireless communication unit 104. The drone 1 receives an instruction such as starting from the base station 50 by the wireless communication unit 104. The base station 50 is configured by a computer.

  The drone 1 can measure the position of the drone 1 itself by the satellite positioning unit 106 and the inertial sensor unit 108. The satellite positioning unit 106 basically measures the position of the drone 1 by receiving positioning radio waves from four or more navigation satellites. The inertial sensor unit 108 measures the position of the drone 1 by accumulating the movement of the drone 1 from the starting point (reference position) using, for example, an acceleration sensor and a gyro sensor. The position information of the drone 1 itself is used for determining the movement route of the drone 1 and autonomous movement, and also for linking image data photographed by the image processing unit 114 and coordinates (position). .

  The drone 1 receives the output from the laser scanner arranged in the housing 2 by the laser scanner unit 110.

  The drone 1 controls the rotation of the propeller 8 (see FIG. 2) connected to each motor 6 (see FIG. 2) by the drive control unit 112, and controls postures such as horizontal movement, air suspension, and tilt. It is like that.

  The drone 1 can acquire an external image by operating the camera 14 (see FIG. 1) by the image processing unit 114.

  The power supply unit 120 is a replaceable rechargeable battery, for example, and supplies power to each unit of the drone 1.

  In addition to various data and programs necessary for autonomous movement, such as data indicating a movement plan for autonomous movement from the starting point to the target position, the storage unit 102 stores the following data and programs.

  The storage unit 102 stores a three-dimensional map. The three-dimensional map shows the shape of the flight region shown in FIG. 1, and is composed of a high-precision and high-density three-dimensional point group. The three-dimensional map is converted into the same coordinate system as the map by associating the position information (latitude, longitude, and altitude) with pixels using GCP (Ground Control Point).

  The generation method of the three-dimensional map is not limited, but is generated by, for example, an SfM (Structure from Motion) image processing method. SfM is a method for obtaining a three-dimensional shape of an object shown in an image from the image. Examples of the SfM software include VisualSFM, Agisoft PhotoScan, and the like. Or you may produce | generate a three-dimensional map from drawings (drawings, such as the expressway 200 and the pier 202A) of a flight area.

  The storage unit 102 stores a flight control program, a positioning program, a reference position determination program, a first position estimation program, a second position estimation program, a third position estimation program, a position determination program, and a route adjustment program. . The CPU 100 and the flight control program are examples of flight control means. The CPU 100 and the positioning program are examples of positioning means. The CPU 100 and the reference position determination program are examples of reference position determination means. The CPU 100 and the first position estimation program are examples of first position estimation means. The CPU 100 and the second position estimation program are examples of second position estimation means. The CPU 100 and the third position estimation program are examples of third position estimation means. The CPU 100, the first position estimation program, the second position estimation program, and the third position estimation program are examples of position estimation means. The CPU 100 and the position determination program are examples of position determination means. The CPU 100 and the route adjustment program are examples of route adjustment means.

  The drone 1 controls autonomous flight of the drone 1 by a flight control program. Specifically, the drone 1 adjusts the electric power supplied to each motor 6 via the drive control unit 112, and flies in a predetermined route and altitude.

  The drone 1 calculates a positioning position A indicating the current position of the drone 1 by a positioning program. When the drone 1 can receive positioning radio waves from four or more navigation satellites, it uses the positioning radio waves to measure the current position to calculate the positioning position A, and determines the current position with a predetermined weight. use. On the other hand, when the drone 1 cannot receive positioning radio waves from four or more navigation satellites, the positioning position A is weighted to 0 even if the positioning result converges, and the positioning position A is used. do not do. The number of navigation satellites less than 4 is an example of the number of navigation satellites less than a predetermined number.

  The drone 1 receives the positioning radio wave at the position where the radio waves for positioning from four or more navigation satellites 300A and the like can be received by the reference position determination program, and measures the current position of the drone 1 for the first reference. Position.

  The drone 1 estimates the current position and calculates the estimated position B using the output from the inertial sensor 20 by the first position estimation program. The drone 1 calculates the estimated position B by accumulating outputs from the acceleration sensor and the gyro sensor that constitute the inertial sensor 20, using the most recently determined current position as a reference position. The drone 1 can continuously calculate the estimated position B by, for example, calculating the estimated position B with the first reference position as the positioning position A and then updating to the newly determined current position. it can.

  The drone 1 estimates the current position based on the captured image data and the three-dimensional map by the second position estimation program, and calculates the estimated position C. The drone 1 captures the outside with the camera 14 to acquire photographed image data, extracts the feature, and compares it with the feature of the three-dimensional map to estimate the current position in the three-dimensional map. Specifically, the drone 1 performs matching between the three-dimensional map and the captured image data, and obtains the three-dimensional coordinates where the features of the two match most, thereby estimating the current position of the drone 1 and the estimated position. C is calculated.

  The drone 1 estimates the current position and calculates the estimated position D using the output (scan data) from the laser scanner by the third position estimation program. The drone 1 performs scan matching between the three-dimensional map and the scan data, finds the three-dimensional coordinates that most closely match the shapes, thereby estimating the current position of the drone 1 and calculates the estimated position D.

  The drone 1 weights the positioning position A and the estimated positions B to D described above by the position determination program to determine the current position.

  Here, as shown in FIG. 4A, when the positioning position A and the estimated positions B to D have a large deviation from the previous determined position and there is a difference exceeding the allowable range, the positioning position and the estimated position are estimated. Since there is a high possibility that the position is incorrect, the weight of the positioning position or the estimated position is reduced. For example, if the position is determined every 0.1 seconds (s), the positioning position or estimated position calculated 0.1 seconds (s) after the previous determined position is 2 meters from the previous determined position. (M) If there is a divergence, the weight of the measurement position or estimated position is reduced.

  Further, as shown in FIG. 4B, as the deviation from the movement state detected by the inertial sensor is larger, the weight of the positioning position or the estimated position is reduced. That is, the output of the inertial sensor is used for weighting evaluation. For example, with reference to the positioning position A1 at time t1 and the positioning position A2 at time t2 after the time Δt has elapsed from time t1, the movement direction from the positioning position A1 to the positioning position A2 and the movement direction detected by the inertial sensor When the difference is large, the weight of the positioning position A is reduced. The same applies to the estimated positions B to D. For example, referring to the estimated position C1 at time t1 and the estimated position C2 at time t2 that has elapsed by time Δt from time t1, the moving direction from the estimated position C1 to the estimated position C2 is referred to. When the difference between the movement direction detected by the inertial sensor and the movement direction is large, the weight of the estimated position C is decreased. The evaluation of the weighting of the measurement position and the estimated position by the inertial sensor, in other words, the evaluation of the reliability of other sensors is performed not only in the movement direction but also in other movement states such as a movement distance. For example, referring to the estimated position D1 at time t1 and the estimated position D2 at time t2 when time Δt has elapsed from time t1, the movement distance from the estimated position D1 to the estimated position D2 and the movement distance detected by the inertial sensor When the difference is large, the weight of the estimated position D is reduced.

  As for the positioning position A, the smaller the number of navigation satellites used, the lower the positioning accuracy. Therefore, as shown in FIG.

  For the estimated position B, as the elapsed time from the previous position determination time becomes longer, the error accumulates and becomes an estimated position with lower accuracy. Therefore, as shown in FIG. Make it smaller.

  The drone 1 adjusts the flight path based on the current position determined by the path adjustment program. The drone 1 determines whether or not there is a predetermined area W for the drone 1 to fly, and calculates an alternative route if there is no space of the predetermined area W.

  The predetermined width W is a spatial extent in which the drone 1 can safely fly, for example, a space in which a cubic shape with one side of 2 meters (m) or more can be stored. For example, as shown in FIG. 5, when the drone 1 moves as indicated by an arrow R1, it determines whether or not the front space has a predetermined width W based on the output of the laser scanner. Assuming that there is a spatial spread of 2 meters or more in the horizontal direction and only explaining the spread in the vertical direction, the drone 1 determines whether the spread in the vertical direction is 2 meters or more. In the example of FIG. 5, the spread in the vertical direction is defined by the altitude Lb and the altitude Lt. The drone 1 determines that there is a predetermined width W if Lt−Lb> 2 (m). On the other hand, if the drone 1 is Lt−Lb ≦ 2 (m), it is determined that the front space does not have the predetermined width W, and an alternative having the width W by referring to the three-dimensional map. Calculate the route. The drone 1 adjusts the measurement conditions, for example, by changing the magnification of the camera 14 while flying on the alternative route.

  If the drone 1 determines that the moving front space has a predetermined width W, the drone 1 moves to the front space while maintaining the horizontal distance α with the object and the vertical distance β. In addition, even if the moving front space has a predetermined width W, if the horizontal distance to the object cannot be secured by α or more and the vertical distance by β or more cannot be secured, the drone 1 is Referring to the three-dimensional map, adjust the measurement conditions, such as calculating an alternative route that can secure the horizontal distance to the object by α or more and the vertical distance by β or more, and changing the magnification of the camera 14 .

  Hereinafter, the operation of the drone 1 will be described with reference to the flowchart of FIG. The drone 1 measures the current position in a state in which positioning radio waves can be received from four or more navigation satellites 300A or the like (step ST1 in FIG. 6), and determines the reference position (step ST2). Subsequently, the drone 1 includes satellite positioning (step ST3A), position estimation based on the output of the inertial sensor (step ST3B), position estimation based on captured image data and a three-dimensional map (step ST3C), and a laser scanner and three-dimensional. Position estimation based on the map (step ST3D) is performed. Subsequently, the drone 1 performs weighting processing of the estimated position calculated in the above-described steps ST3A to ST3D (step ST4), and determines the current position (step ST5). In the weighting process in step ST4, weighting evaluation by an inertial sensor is also performed. The drone 1 determines whether or not the mission is finished (step ST6). If the mission is not finished, steps ST3A to ST3D and steps ST4 to ST6 are repeated.

  Note that the present invention is not limited to the above-described embodiments, and modifications, improvements, and the like within a scope in which the object of the present invention can be achieved are included in the present invention.

1 Unmanned Aircraft 2 Housing 6 Motor 20 Inertial Sensor 22 Antenna

Claims (7)

An unmanned air vehicle that obtains thrust by rotating a propeller,
A positioning means for calculating a positioning position by positioning a current position using radio waves for positioning from a navigation satellite;
Position estimation means for estimating the current position and calculating the estimated position by a plurality of types of position estimation methods that do not use the positioning radio wave;
Position determination means for performing weighting in the estimated position estimated by the positioning position and the estimated position, or a plurality of types of the position estimation methods, and determining a current position;
Unmanned aerial vehicle with. The position estimating means includes
First estimation means for estimating a current position based on an output of an inertial sensor and calculating a first estimated position;
Second estimation means for estimating a current position based on three-dimensional data and photographing data obtained by photographing with a camera and calculating a second estimated position;
Third estimation means for estimating a current position based on the three-dimensional data and the output of the laser scanner and calculating a third estimated position;
The unmanned aerial vehicle according to claim 1, comprising at least one of:   The position determining means is configured to determine the current position based on the estimated position without using the positioning position when the number of the navigation satellites capable of receiving the positioning radio waves is less than a predetermined number. The unmanned aerial vehicle according to claim 2, wherein   The position determination means exceeds the allowable range when there is a difference exceeding the allowable range from the estimated position estimated immediately before in any of the estimated positions estimated in the plurality of types of position estimation methods. The unmanned aerial vehicle according to claim 2 or 3, wherein the unmanned air vehicle is configured not to use the estimated position. The position determining means is configured to perform the weighting based on an output of an inertial sensor.
The unmanned aerial vehicle according to any one of claims 1 to 4. An unmanned air vehicle that gains thrust by the rotation of a propeller,
A positioning step for calculating a positioning position by positioning a current position using a positioning radio wave from a navigation satellite;
A position estimation step of calculating an estimated position by estimating a current position by a plurality of types of position estimation methods that do not use the positioning radio wave; and
A position determination step of performing weighting in the estimated position estimated by the positioning position and the estimated position, or a plurality of types of the position estimation methods, and determining a current position;
Perform unmanned flight way. A computer that controls an unmanned aerial vehicle that gains thrust by rotating a propeller.
Positioning means for calculating the positioning position by positioning the current position using radio waves for positioning from navigation satellites;
Position estimation means for estimating the current position and calculating an estimated position by a plurality of types of position estimation methods that do not use the positioning radio wave;
Position determining means for performing weighting in the estimated position estimated by the positioning position and the estimated position, or a plurality of types of the position estimating methods, and determining a current position;
Unmanned flight program to function as.