CN109341695B

CN109341695B - Indoor unmanned aerial vehicle navigation method based on indoor graph calibration

Info

Publication number: CN109341695B
Application number: CN201811363381.4A
Authority: CN
Inventors: 陈旋; 王冲; 张�荣
Original assignee: Jiangsu Aijia Household Products Co Ltd
Current assignee: Jiangsu Aijia Household Products Co Ltd
Priority date: 2018-11-15
Filing date: 2018-11-15
Publication date: 2022-04-26
Anticipated expiration: 2038-11-15
Also published as: CN109341695A

Abstract

The invention discloses an indoor unmanned aerial vehicle navigation system based on indoor type graph calibration. After the initial position and the angle of an unmanned aerial vehicle head are determined, flight tracks are continuously calibrated with pixel points in a family pattern, the flight track vector of the unmanned aerial vehicle is calculated through the calibration pixel points, and the deviation angle and the displacement in the flight process of the unmanned aerial vehicle are calculated through a scale, so that the unmanned aerial vehicle is applied to the real-time navigation in the fields of controlling the indoor construction, the cruise control and the like of an accurate unmanned aerial vehicle monitoring room. The indoor unmanned aerial vehicle based on the indoor type graph calibration has the advantages of low navigation calculated amount, high accuracy, high real-time performance, low power consumption, low cost and the like.

Description

Indoor unmanned aerial vehicle navigation method based on indoor graph calibration

Technical Field

The invention discloses an indoor unmanned aerial vehicle navigation system based on indoor type graph calibration.

Background

In the existing unmanned aerial vehicle automatic navigation technology, under the condition that an indoor GPS signal is unavailable, the calculation amount based on a multi-view vision system is large, the cost is high, the real-time performance is difficult to guarantee, and a GPU or a high-performance CPU is required to participate in calculation; and in the hard-mounting process of the navigation based on the radar, the accuracy is difficult to reach the requirement of plus or minus 0.1m due to the influence of factors such as dust, and meanwhile, the calculation amount caused by the factors such as dust is increased, so that the RTOS real-time system cannot meet the requirement.

Disclosure of Invention

The invention discloses an indoor unmanned aerial vehicle navigation system based on indoor type graph calibration. The method has the advantages of low calculation amount, high accuracy, high real-time property, low power consumption, low cost and the like.

An indoor unmanned aerial vehicle navigation method based on indoor type graph calibration comprises the following steps:

step 1, sequentially calibrating position points on a simulated flight track of the unmanned aerial vehicle in a house type diagram, and setting the coordinate positions of the position points in the house type diagram as (xi, yi), i being 0, 1, 2, … …, n;

step 2, calculating a flight track vector between two adjacent position points;

and 3, calculating the actual flying distance between the position points according to the scale of the household graph.

In one embodiment, let the initial vector of the drone be the unit vector (1, 0).

In one embodiment, the initial position of the drone head is set at a 90 ° angle to the direction of the door.

In one embodiment, in the step 2, the flight rotation direction is calculated by vector cross-product of two adjacent position coordinates.

In one embodiment, the direction of rotation is

In one embodiment, in step 3, distance ═ i (x) is passed_n-x_n-1，y_n-y_n-1) And | ratio calculates the flight distance between adjacent points.

In one embodiment, the drone navigates through the GSP to the initial position in step 1 that requires navigation with a custom-type map.

In one embodiment, the unmanned aerial vehicle keeps away the barrier through 6 infrared sensor around through about from top to bottom.

In one embodiment, when the infrared sensor reports a high level interruption original flight instruction, obstacle avoidance navigation is performed in the opposite direction, and navigation is continued after the navigation point is recalibrated.

In one embodiment, the unmanned aerial vehicle is connected with the server through the wireless transmission module, and uploads the data to the server for data analysis and monitoring.

Advantageous effects

Under the scene that the indoor precision requirement is high, the real-time requirement is high, and meanwhile, the interference factors such as dust and the like in the hard-mounting process are many, the problems can be effectively solved through the method, and meanwhile, the method has the advantages of low power consumption and low cost of hardware deployment, and the RTOS system can be used for production.

Drawings

FIG. 1 is a flow chart of a navigation method of the present invention;

FIG. 2 is a simplified coordinate system space;

FIG. 3 is a complex coordinate system space;

FIG. 4 is a trace line set in the house layout;

FIG. 5 is a diagram illustrating calculation of missing information of included angle of vector by dot product;

fig. 6 is a hardware module diagram.

Detailed Description

Example 1

The indoor unmanned aerial vehicle navigation system based on the user type diagram calibration calculates the indoor navigation track of the unmanned aerial vehicle by calibrating the pixel points and utilizing the scale of the user type diagram. The overall calculation method is shown in fig. 1, and the unmanned aerial vehicle navigation algorithm is realized as follows:

as shown in fig. 2, firstly, the unmanned aerial vehicle is navigated to an indoor initial position by using the GPS, the flight trajectory of the unmanned aerial vehicle is continuously navigated through an indoor floor plan, an initial position of a nose of the unmanned aerial vehicle forms a 90-degree included angle with a direction of a door, after the unmanned aerial vehicle enters a door of a scene, the direction in which a plane of the door is defined is the direction of the door, and after the unmanned aerial vehicle directly and vertically enters the scene, the direction in which the nose is located refers to the initial direction of the unmanned aerial vehicle, so that the initial direction is directly perpendicular to the door, therefore, the initial vector is set as a unit vector (1,0), a pixel point position is set as (xi, yi), and the nose vector is selected as the unit vector as shown in fig. 2, so that complexity and additional calculation amount caused by coordinate system conversion in the coordinate system space calculation process of fig. 3 can be avoided.

Next, the trajectory needs to be determined. In the house type diagram, the set position points which need to pass through in sequence are respectively: (x)₂，y₂)……(x_n，y_n) And the track is as shown in fig. 4, the flight track vector of the unmanned aerial vehicle is calculated through the calibration pixel points, and the deviation angle and the displacement of the unmanned aerial vehicle in the flight process are calculated through the scale. And calibrating n pixel points, wherein the actual flight track is n-1 times. Thus, the flight vector at each point is then:

(x₂-x₁，y₂-y₁)，(x₃-x₂，y₃-y₂)，(x_n-x_n-1，y_n-y_n-1)

when using vector dot product to calculate the contained angle that unmanned aerial vehicle flies, be respectively:

(1，0)·(x₂-x₁，y₂-y₁)，

(x₂-x₁，y₂-y₁)·(x₃-x₂，y₃-y₂)，…

(x_n-1-x_n-2，y_n-1-y_n-2)·(x_n-x_n-1，y_n-y_n-1)

the vector angle theta can only be used for calculating an offset angle, as shown in fig. 5, included angles between a machine head vector and target vectors 1 and 2 are theta, and if the rotation direction of the unmanned aerial vehicle is to be determined, clockwise or counterclockwise rotation needs to be calculated, and the vector cross product is used as supplement.

According to the right-hand rule

Indicating clockwise and less than 0 indicating counterclockwise.

The actual flying distance is:

distance＝|(x_n-x_n-1，y_n-y_n-1)|·ratio

ratio represents the scale, which is equal to the resolution of the floor plan over the actual distance.

Based on the above method, the hardware arrangement is as shown in fig. 6: the unmanned aerial vehicle is navigated to a construction site needing to be monitored through the GPS outdoors, and after entering the room, the unmanned aerial vehicle is navigated through the real-time navigation system in the invention 1, data is acquired, and the data is reported to the server side through the 4G module for data analysis and monitoring. Obstacle avoidance is carried out through 6 infrared sensors which are arranged up, down, left, right, front and back; therefore, the method is applied to the fields of controlling the indoor construction of the precise monitoring of the unmanned aerial vehicle, performing regular inspection and cruising and the like; the main controller stm32f407 calculates the distance, the two-dimensional vector included angle and the three-dimensional Euler angle in the flight process, sends a flight instruction through a URAT serial port, interrupts the original flight instruction when the infrared sensor reports a high level, conducts obstacle avoidance navigation in the opposite direction, and continues navigation after the navigation point is calibrated again.

Claims

1. An indoor unmanned aerial vehicle navigation method based on indoor type graph calibration is characterized by comprising the following steps:

step 1, in a house type diagram, sequentially calibrating position points on a simulated flight track of the unmanned aerial vehicle, and setting coordinate positions of the position points in the house type diagram as (x)_i,y_i)，i=0,1,2,……,n；

Step 2, calculating a flight track vector between two adjacent position points;

step 3, calculating the actual flying distance between each position point according to the scale of the house-type diagram;

setting an initial vector of the unmanned aerial vehicle as a unit vector (1, 0);

setting an initial position of an unmanned aerial vehicle head to form a 90-degree included angle with the direction of a door;

in the step 2, the flight rotation direction is obtained through vector cross-product calculation of two adjacent position coordinates;

the direction of rotation is

；

In step 3, by

Calculating the flying distance between adjacent points; ratio represents the scale, which is equal to the resolution of the floor plan over the actual distance.

2. The indoor unmanned aerial vehicle navigation method based on calibration of a user-type map as claimed in claim 1, wherein the unmanned aerial vehicle navigates to the initial position in step 1 where the user-type map navigation is required through the GSP.

3. The indoor unmanned aerial vehicle navigation method based on house type map calibration as claimed in claim 1, wherein the unmanned aerial vehicle avoids obstacles through 6 infrared sensors up, down, left, right, front and back.

4. The indoor unmanned aerial vehicle navigation method based on house type map calibration as claimed in claim 1, wherein when an infrared sensor reports a high level and interrupts an original flight instruction, obstacle avoidance navigation is performed in the opposite direction, and after a navigation point is recalibrated, navigation is continued.

5. The indoor unmanned aerial vehicle navigation method based on house type map calibration as claimed in claim 1, wherein the unmanned aerial vehicle is connected with the server through a wireless transmission module, and data is uploaded to the server for data analysis and monitoring.