CN113218403B - AGV system of inertia vision combination formula location - Google Patents
AGV system of inertia vision combination formula location Download PDFInfo
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- CN113218403B CN113218403B CN202110528533.7A CN202110528533A CN113218403B CN 113218403 B CN113218403 B CN 113218403B CN 202110528533 A CN202110528533 A CN 202110528533A CN 113218403 B CN113218403 B CN 113218403B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/60—Electric or hybrid propulsion means for production processes
Abstract
The invention provides an AGV (automatic guided vehicle) system with inertial vision combined positioning, wherein a control device comprises a camera group, an upper computer, a lower computer and a strapdown inertial navigation integrator which are sequentially connected; the upper computer collects data of the camera group in real time and plans a real-time path according to surrounding road conditions; the lower computer controls the vehicle body to move, and nearby elements are identified by using the gray level group and the OpenMV group; the upper computer and the lower computer are communicated with each other; the strapdown inertial navigation integrator is respectively connected with the capacitance-inductance pair, the OV7725 camera, the gray sensor, the gyroscope, the magnetometer and the Apriltag code. The invention adopts various sensors of different types, sets identification marks of various different types in a working scene, fully manufactures the optimal use environment of various sensors, and improves the positioning precision to the level which can be reached by a laser positioning technology under the condition of not increasing too much cost.
Description
Technical Field
The invention belongs to the technical field of unmanned driving, and particularly relates to an inertial vision combined positioning AGV system.
Background
An automated Guided vehicle agv (automated Guided vehicle) is an unmanned vehicle. The method is characterized in that position information of a vehicle and a target object is obtained through a vehicle-mounted sensor or communication equipment, and an automatic driving carrier is manufactured along a target driving route and a parking position according to a programmed algorithm or a control instruction sent by a central dispatching system. The AGV is widely applied to docks, warehouses, factory workshops, flexible production systems (FMS), flexible handling systems and automatic warehouses and serves as key equipment for logistics system modernization.
There are two navigation ways for an AGV: a fixed path and a free path.
Currently, AGV systems can be classified into electromagnetic guidance and tape guidance according to the guidance mode.
In foreign countries, mobile robots based on mecanum wheels have certain achievements through researches of colleges and scientific research institutions, and all robot companies also develop omnidirectional mobile robots on the basis of original double-wheel differential robots. The related research on the Mecanum wheel mainly focuses on the fields of omnidirectional motion modeling, damping suspension design, omnidirectional mobile robot platform research and development, intelligent control and the like.
The research on omnidirectional mobile robots such as Mecanum wheels is relatively late in China, the main research fields comprise omnidirectional mobile robot design, vibration reduction suspension design, motion control and error elimination, fuzzy PID control, accurate control and the like, and the intelligent navigation is less involved.
The conventional AGV system with a fixed path often cannot solve the problems of sudden road blockage in the actual environment and junction congestion during combined operation of a plurality of AGV systems because the traveling path is limited; however, the laser SLAM and the visual SLAM are not mature, the laser SLAM is not good at positioning in a dynamic environment, has poor repositioning capability and lacks loop detection capability, and the visual SLAM needs to use a complex algorithm to process an actual image at present. In short, a high-precision positioning component is expensive, and a low-cost sensor has a large error.
Disclosure of Invention
The invention aims to provide an AGV based on a strapdown inertial navigation system, which can integrate data of various sensors, complete positioning and navigation work of high-cost and high-precision sensors by using relatively low cost, perform optimal path planning by using an automatic control program and complete cargo transportation and logistics transfer.
The specific technical scheme is as follows:
the AGV system with the inertial vision combined positioning comprises a control device, a power supply device and a physical execution part;
the control device comprises a camera group, an upper computer, a lower computer and a strapdown inertial navigation integrator which are sequentially connected;
the upper computer collects data of the camera group in real time and plans a real-time path according to surrounding road conditions;
the lower computer controls the vehicle body to advance, and nearby elements are identified by using the gray level group and the OpenMV group;
the upper computer and the lower computer are communicated with each other;
the strapdown inertial navigation integrator is respectively connected with the capacitance-inductance pair, the OV7725 camera, the gray sensor, the gyroscope, the magnetometer and the Apriltag code;
the capacitive inductance pair on the vehicle collects an electric signal through an exciting electromagnetic field and judges the position of the vehicle body relative to the electromagnetic wire to complete the tracking of the electromagnetic wire so as to realize electromagnetic guidance;
the OV7725 camera is used for collecting road surface visual information, feeding the road surface visual information back to the lower computer and controlling the road surface visual information;
the gray level sensor is an analog sensor which detects black markers on the ground by utilizing different ground light reflection intensities of different colors and is used for positioning with the accuracy within 1 cm;
the gyroscope, the accelerometer and the magnetometer are integrated on the MPU9250 chip, and real-time three-axis attitude angles are calculated by reading three-axis acceleration, three-axis angular acceleration and three-axis magnetic field original data;
an Apriltag code for identifying a designated marker during operation;
the power supply device comprises a power module and a 6S lithium battery, and the power module and the 6S lithium battery are used for respectively supplying power to electric equipment;
the physical execution part is connected with the lower computer and comprises a motor driving circuit, and the motor driving circuit respectively provides power for the motor, the Mecanum wheel and the electric dragging device.
Wherein the camera group comprises a plurality of OV2710 cameras; the model of the upper computer is i.MX6Q; the lower computer is MK66 FX.
The motor driving circuit adopts a 8701 driving circuit, a half-bridge motor driving circuit is built to supply electromagnet energy, and the motor driving circuit further comprises a 3V3 voltage acquisition circuit, a voltage stabilizing diode BZT52C3V3 and a 74HC125 buffer circuit, and plays a role of a grating.
Compared with the prior art, the invention has the advantages that:
1. the sensors of various types are adopted, and the identification marks of various different forms are arranged in a working scene, so that the optimal use environment of various types of sensors is fully manufactured.
2. The method avoids using expensive positioning and measuring modules, and improves the positioning precision to the order of magnitude which can be reached by the laser positioning technology under the condition of not increasing too much cost. For example, Apriltag codes and logo recognition of a grayscale sensor can effectively solve the problem of drift caused by long-time operation of a gyroscope and an accelerometer.
Drawings
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a schematic diagram of a power supply network of the present invention;
FIG. 3 is a schematic view of a Mecanum wheel of the present invention;
FIG. 4 is a block diagram of the closed-loop control of the motor speed of the present invention.
Detailed Description
As shown in FIG. 1, the AGV system with inertial vision combined positioning comprises a control device, a power supply device and a physical execution part;
the control device comprises a camera group, an upper computer, a lower computer and a strapdown inertial navigation integrator which are sequentially connected;
the camera group comprises a plurality of OV2710 cameras;
the upper computer is i.MX6Q; the lower computer is MK66 FX; MX 6Quad series is a platform with four cores, the operating frequency is up to 1.2GHz, and the LPDDR2 is supported by 1MB L2 cache and 64-bit DDR3 or 2 channel 32; the upper computer collects data of the camera group in real time and plans a real-time path according to surrounding road conditions; the lower computer controls the vehicle body to move, and nearby elements are identified by using the gray level group and the OpenMV group;
the upper computer and the lower computer are communicated with each other, if a single controller fails, the vehicle body can be directly stabilized through communication, the alarm is given, the vehicle body is locked automatically, and precautionary measures are designed for emergency situations of the vehicle body;
the strapdown inertial navigation integrator is respectively connected with the capacitance-inductance pair, the OV7725 camera, the gray sensor, the gyroscope, the magnetometer and the Apriltag code;
the capacitive inductance pairs are laid on the ground and are electrified to exchange current, so that the capacitive inductance pairs on the vehicle can acquire electric signals through exciting an electromagnetic field and judge the position of the vehicle body relative to the electromagnetic wire to complete the tracking of the electromagnetic wire, thereby realizing electromagnetic guidance;
the OV7725 camera is used for collecting road surface visual information, feeding the road surface visual information back to the lower computer and controlling the road surface visual information;
the gray sensor is an analog sensor for detecting black markers on the ground by utilizing different light reflection intensities of different colors of ground, and is used for positioning within 1cm in precision.
The gyroscope, the accelerometer and the magnetometer are integrated on the MPU9250 chip, and real-time three-axis attitude angles are calculated by reading three-axis acceleration, three-axis angular acceleration and three-axis magnetic field original data;
the recognition of the Apriltag code is fast and error-free compared with the method that a camera is used for judging the designated marker in the operation process. By predefining the information of each Apriltag code and placing the corresponding two-dimensional code beside a special element, the Apriltag codes can play the roles of a road sign and a direction board when the AGV system works, for example, if the X two-dimensional code is defined as a storage place N, when the AGV system is far away from the N place, if the destination is N, the task can be set to detect the X two-dimensional code and consider the X two-dimensional code as the destination.
The power supply device comprises a power module and a 6S lithium battery, the working voltage is 22.2V-24.8V, the discharge rate is 25C, the LM2596 module is used for stabilizing 6V voltage for the steering engine, the 3.3V voltage is used for the minimum system and the camera, and the MP1584 module is used for stabilizing 5V voltage for the encoder and part of the sensors.
The physical execution part is connected with the lower computer and comprises a motor driving circuit which respectively provides power for the motor, the Mecanum wheel and the electric dragging device;
the physical execution part is powered by motor drive and electromagnet drive. As shown in fig. 2, a 8701 driving circuit is used, which is used for supplying power to the electromagnet to draw the object to be transported by building a half-bridge motor driving circuit; a 3V3 voltage acquisition circuit; a zener diode BZT52C3V3 for enabling the DRV8701nSLEEP pin; the 74HC125 buffer circuit plays the role of a light grating, namely, the current of the working circuit is prevented from flowing backwards to influence the power supply circuit.
The electric driving device is mainly used for carrying goods and is realized by using an electromagnet, and a DRV8701 is used as an electromagnet driving chip. The exercise device uses mecanum wheels that allow for omnidirectional movement and is equipped with a shock absorbing system to address the case where the four wheel redundant structure is virtually grounded.
When the AGV system carries goods, the two-dimensional code information on the goods can be read or generated into a carrying path according to an upper computer algorithm, and then the goods are transported to an appointed place through the strapdown inertial navigation system.
And (3) control algorithm aspect:
the system adopts a distributed control mode based on serial ports, namely, an upper layer algorithm and a bottom layer control respectively use different single-chip microcomputers, namely an upper computer and a lower computer, and the functions are mutually independent and dispersed. The method has the advantages of improving control efficiency, shortening control time, reducing configuration requirements and cost of the single chip microcomputer, increasing data encryption and verification during communication, and ensuring the safety and accuracy of centralized control.
The system uses a scheme in which four wheels are Mecanum wheels, as shown in U of FIG. 3 1234 Showing the component velocity, V, provided to the vehicle by each wheel as the AGV system advances 1234 Indicating the deviated wheel component speed due to the non-ideal characteristics of the wheel; the four-wheel vehicle has the advantages of capability of carrying out omnidirectional control, small turning radius, no need of turning space and saving of turning time of the common four-wheel vehicle. The implementation mode is as follows, under the ideal condition, all wheels rotate clockwise and can let the AGV system advance, at this moment, change upper left and lower right wheel into anticlockwise rotation and can let the AGV system translate left, and translation right and retreat control mode will be the direction of rotation and translation left and advance the reverse of every wheel. The process is realized on codes, firstly, the output duty ratio of each drive and the actual rotating speed of a motor are normalized during joint debugging, the rotating speeds of four wheels are ensured to be the same, and then, the rotating speeds of the four wheels are recorded and recorded by taking forward, backward and left-right translation as routines. Finally, the rotation speeds of the four wheels are debugged and recorded by taking clockwise rotation and anticlockwise rotation as a routine. In actual use, the required rotating speed of each wheel can be obtained through decomposition of the motion process, and the omnidirectional control can be achieved through a wheel encoder and a drive and a PID control algorithm of a single chip microcomputer.
In the aspect of motor speed control: an incremental photoelectric encoder using the AB term is used. The function of which is to determine the direction and angle of rotation of the wheel (typically measured in turns). The motor rotating speed closed-loop control block diagram is shown in fig. 4, the upper computer gives a motor rotating speed set value, and a signal of the motor rotating speed set value enters the direct current motor driver after being subjected to PI correction. The current is amplified through driving and supplied to the direct current motor, and meanwhile, the speed of the direct current motor is collected and fed back to the PI controller for speed correction.
In the aspect of angle calculation: the JY-901 module is used for measuring 9 data in total of the acceleration, the angular acceleration and the magnetometer, each group of data can obtain a function curve along with time, after Kalman filtering processing is carried out, integration processing is carried out, the speed and the angular velocity can be obtained, and the acceleration and the angular acceleration can be obtained by integration again. But inexpensive low-precision measurement modules tend to suffer from drift phenomena. In order to solve the problem, the system is provided with a photoelectric pair tube and a camera with an Apriltag code identification function. The ground and the track are specially processed, and a beacon is arranged per unit length (for example, 1m), so that the drift of the odometer is corrected.
In the camera processing aspect: an OV7725 camera is used, and in order to increase the processing speed, the system uses a single MCU to process the image, and the image information is stored in GRAM in the LCD. Four OV7725 cameras are arrayed on the circumference of the system and used for achieving all-around view identification. The image processing mode mainly uses a jump detection algorithm and a jump detection algorithm after differentiation. The jump detection algorithm can obviously capture the contour lines in the image and is used for assisting in calculating the terrain and the size of the conveyed object.
And (3) path planning:
the time of each transport task can be roughly determined according to the path bit vector and the transport type, and when the task quantity is small, the problem can be solved by using a linked list processing mode of 'processing while receiving'.
When the transport is multitasking and there is one AGV system operating. The system gives variable values according to the task urgency degree, and then selects the task closest to the conveying point or the most urgent task for processing through weighting.
When the transport tasks are multiple and a plurality of AGV systems operate simultaneously, the system can adopt a token control method to carry out central regulation and control. Each trunk road and the regions with dense and repeated carrying lines have a token value, and when the AGV system executes a carrying task, all the token values of the moving lines are transmitted to the central processing unit through the Bluetooth module. When the token value is repeated, the fact that the planned path of the AGV system is repeated and collision is possible is shown, and at the moment, the central control allocates the accounting times of the AGV system to avoid in turn. The method has the advantages that the same-level communication module is not needed, and the conditions of collision avoidance and even collision danger are avoided. In particular, when the task size is extremely large or an emergency task occurs, the low-priority AGV system will actively avoid the high-priority AGV system.
Claims (3)
1. The AGV system comprises a control device, a power supply device and a physical execution part;
the control device comprises a camera group, an upper computer, a lower computer and a strapdown inertial navigation integrator which are sequentially connected;
the upper computer collects data of the camera group in real time and plans a real-time path according to surrounding road conditions;
the lower computer controls the vehicle body to move, and nearby elements are identified by using the gray level group and the OpenMV group;
the upper computer and the lower computer are communicated with each other;
the strapdown inertial navigation integrator is respectively connected with the capacitance-inductance pair, the OV7725 camera, the gray sensor, the gyroscope, the magnetometer and the Apriltag code;
the capacitive inductance pair on the vehicle collects an electric signal through an exciting electromagnetic field and judges the position of the vehicle body relative to the electromagnetic wire to complete the tracking of the electromagnetic wire so as to realize electromagnetic guidance;
the OV7725 camera is used for collecting road surface visual information, feeding the road surface visual information back to the lower computer and controlling the road surface visual information;
the gray sensor is an analog sensor for detecting black markers on the ground by utilizing different light reflection intensities of grounds with different colors, and is used for positioning within 1cm in precision;
the gyroscope, the accelerometer and the magnetometer are integrated on the MPU9250 chip, and real-time three-axis attitude angles are calculated by reading three-axis acceleration, three-axis angular acceleration and three-axis magnetic field original data;
an Apriltag code for identifying a designated marker during operation;
the power supply device comprises a power module and a 6S lithium battery, and the power module and the 6S lithium battery are used for respectively supplying power to electric equipment;
the physical execution part is connected with the lower computer and comprises a motor driving circuit, and the motor driving circuit respectively provides power for the motor, the Mecanum wheel and the electric dragging device;
the control method is characterized by comprising the following steps:
the Apriltag codes play roles of road signs and direction boards during operation of an AGV system by predefining information of each Apriltag code and placing a corresponding two-dimensional code beside a special element;
when the AGV system carries goods, a carrying path is generated according to an upper computer algorithm or two-dimensional code information on the goods is read, and then the goods are transported to a specified place through the strapdown inertial navigation system;
and (3) control algorithm aspect:
the system adopts a distributed control mode based on serial ports, namely, an upper layer algorithm and a bottom layer control respectively use different singlechips, namely an upper computer and a lower computer, and mutually independent functions are dispersed;
the system adopts a scheme that four wheels are Mecanum wheels; all the wheels rotate clockwise to enable the AGV system to advance, at the moment, the upper left wheel and the lower right wheel are changed into anticlockwise rotation to enable the AGV system to translate leftwards, and the right translation and retreat control mode is that the rotation direction of each wheel is opposite to the left translation and advance; firstly, normalizing the output duty ratio of each drive and the actual rotating speed of a motor during joint debugging to ensure that the rotating speeds of the four wheels are the same, and then recording the rotating speeds of the four wheels by taking forward, backward and left-right translation as routines and recording the rotating speeds; finally, the rotation speeds of the four wheels are debugged and recorded by taking clockwise rotation and anticlockwise rotation as a routine; the device is decomposed through a motion process in actual use; the required rotating speed of each wheel is obtained, and the PID control algorithm of the single chip microcomputer achieves omnidirectional control through the wheel encoder and the drive;
in the aspect of motor speed control: incremental photoelectric encoders using the AB term; the function is to judge the rotation direction and angle of the wheel; the upper computer gives a set value of the rotating speed of the motor, and a signal of the set value enters a direct current motor driver after being subjected to PI correction; the current is amplified through driving and supplied to the direct current motor, and meanwhile, the speed of the direct current motor is collected and fed back to the PI controller for speed correction;
angle resolving aspect: using a JY-901 module to measure 9 data in total of the acceleration, the angular acceleration and the magnetometer, obtaining a function curve from each group of data along with time, carrying out Kalman filtering treatment, then carrying out integration treatment to obtain the speed and the angular velocity, and carrying out integration again to obtain the acceleration and the angular acceleration; the photoelectric geminate transistors and the camera with the Apriltag code identification function are mounted; processing the ground and the track, and setting a beacon per unit length to correct drift of the odometer;
in the aspect of camera processing: an OV7725 camera is adopted, an independent MCU is used for processing images, and image information is stored in GRAM in an LCD; four OV7725 cameras are arrayed on the circumference of the system and used for realizing omnibearing visual field identification; the image processing mode mainly uses a jump detection algorithm and a jump detection algorithm after differentiation; the jumping detection algorithm obviously captures the contour line in the image and is used for assisting in calculating the terrain and the size of the conveyed object;
and (3) path planning:
the time of each transport task is determined according to the path position vector and the transport type, and when the task amount is small, a linked list processing mode of 'processing while receiving' is used;
when the carrying tasks are multiple and one AGV system operates; the system gives variable values according to the task urgency degree, and then selects the task closest to the carrying point or the most urgent task for processing through weighting;
when the carrying tasks are multiple and a plurality of AGV systems operate simultaneously, the system adopts a token control method to carry out central regulation and control; each trunk road and the areas with densely repeated carrying lines have a token value, and when the AGV system executes a carrying task, all the token values of the moving lines are transmitted to the central processing unit through the Bluetooth module; when the token value is repeated, the AGV system planning path is repeated, collision is possible, and at the moment, the central dispatching of the accounting times of the AGV system is adopted for avoiding in turn; when the task amount has an emergency task, the low-priority AGV system can actively avoid the high-priority AGV system.
2. The method of controlling an inertial vision combined positioned AGV system according to claim 1, characterised in that said camera group comprises a plurality of OV2710 cameras; the model of the upper computer is i.MX6Q; the lower computer is MK66 FX.
3. The method of claim 1, wherein said motor drive circuit is a 8701 drive circuit, a half-bridge motor drive circuit is configured to provide power to the electromagnet, and further comprising a 3V3 voltage acquisition circuit, a zener diode BZT52C3V3, and a 74HC125 buffer circuit functioning as a light barrier.
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