CN115562262A - Automatic navigation control method and device for AGV - Google Patents
Automatic navigation control method and device for AGV Download PDFInfo
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Abstract
The invention discloses an automatic navigation control method and device for an AGV. Receiving positioning data of a laser radar sensor and positioning data of an incremental encoder; filtering the two types of positioning data respectively, and fusing the two types of filtered data to obtain a final AGV position coordinate; establishing a pose error tracking model of the current pose and the expected pose of the AGV, designing a sliding mode surface according to the pose error tracking model, adding an approach law to obtain control output of a sliding mode controller, controlling a driving motor and a steering motor to act according to the control output to enable the AGV to approach the expected pose, and controlling the AGV to converge to the expected pose by designing an inversion sliding mode controller. The invention adopts two sensors to combine positioning and combines improved sliding mode control, thereby not only improving the positioning stability and reliability, but also realizing the driving control of the AGV quickly and improving the tracking precision.
Description
Technical Field
The invention relates to the technical field of automatic guided vehicles, in particular to an automatic navigation control method and device for an AGV and a storage medium.
Background
An Automated Guided Vehicle (AGV) performs autonomous movement in an intelligent and information-based factory, and thus requires high-precision control and high stability and reliability.
In the actual operation debugging process, the following problems mainly exist: 1. the key technology of the AGV is how to acquire the position of the AGV in the movement process of the AGV, and the positioning problems that the position information of a controller is inaccurate or lost and the like often occur; 2. due to the fact that data between hardware building have certain interference problems, the problem that control motion precision is not high occurs in the partial AGV operation process; 3. the non-ideality of the actual system in all aspects causes delay in the switching of the variable structure control, and the system state is difficult to strictly slide along the sliding mode surface, resulting in poor control accuracy.
Disclosure of Invention
The invention aims to provide an automatic navigation control method and device for an AGV, which are used for solving the problems of inaccurate positioning of the AGV due to inaccurate or lost position information and low control movement precision of the AGV in the running process.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, a method for controlling automatic navigation of an AGV includes:
receiving AGV positioning data measured by a laser radar sensor and AGV positioning data measured by an incremental encoder in an interval period of two adjacent scans of the laser radar sensor;
filtering the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder respectively, and fusing the two kinds of filtered data to obtain a final AGV position coordinate;
establishing a pose error tracking model of the current pose and the expected pose of the AGV, designing a sliding mode surface according to the pose error tracking model, adding an approach law to obtain control output of a sliding mode controller, controlling a driving motor and a steering motor to execute corresponding actions according to the control output so that the AGV approaches the expected pose, and controlling the AGV to converge to the expected pose by designing an inversion sliding mode controller.
Further, the filtering processing is respectively performed on the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder, and the filtering processing includes:
selecting the length of a filtering window, carrying out least square polynomial fitting on data in the window to obtain a central curve of the data, and carrying out smoothing treatment on the central curve.
Further, the fusing the two kinds of filtered data includes:
if the AGV position coordinates obtained by the laser radar sensor in the interval period of the adjacent two-time scanning are the same, fusing the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder in the interval period of the adjacent two-time scanning of the laser radar sensor according to the following formula to obtain the final AGV position coordinates:
agv_x＝x 0 +v encoder for encoding a video signal cosδ(t 2 -t 1 )
agv_y＝y 0 +v Encoder for encoding a video signal sinδ(t 2 -t 1 ) (1)
In the formula, (AGV _ x, AGV _ y) represents the position coordinates of the AGV obtained by fusing two types of positioning data, (x) 0 ，y 0 ) AGV for lidar sensor feedback at t 0 Position coordinates of time of day, v Encoder for encoding a video signal The forward speed of the AGV fed back by the incremental encoder is delta, the steering angle of a single steering wheel of the AGV is represented by t 1 、t 2 Respectively corresponding time moments of adjacent two-time scanning of the laser radar sensor.
Further, the position error tracking model of the current position and the expected position of the AGV is as follows:
in the formula (I), the compound is shown in the specification,
are respectively x e 、y e 、θ e Derivative with respect to time, x e 、y e 、θ e Respectively, a transverse displacement error, a longitudinal displacement error and a course angle deviation under an XOY coordinate system, and v is AGVThe advancing speed of the single steering wheel, delta is the steering angle of the single steering wheel, theta is the course angle of the AGV,
are respectively x r 、y r 、θ r Derivative with respect to time, (x) r 、y r 、θ r ) Expected pose for AGV, where x r 、y r Expected coordinate values, theta, of the AGV on the X-axis and Y-axis, respectively r Is the expected heading angle of the AGV;
the step of designing a sliding mode surface according to the pose error tracking model and adding an approach law to obtain the control output of the sliding mode controller comprises the following steps:
slip form surface S is respectively designed for transverse displacement error and longitudinal displacement error 1 、S 2 ：
In the formula, c 1 、c 2 Parameters of an integral sliding mode surface;
the designed approach rate is:
in the formula, k 1 、k 2 A coefficient for the designed approach rate;
substituting (6) and (7) into (5) to calculate AVG expected course angle theta r ：
Design slip form surface S for course angle deviation 3 ：
S 3 ＝θ e +c 3 ∫θ e (9)
Law of approach
In the formula, c 3 、k 3 Epsilon is a coefficient of a designed sliding mode surface and an approach rate;
and (5) integrating the formulas (5) to (10) to obtain a control output u of the sliding mode controller:
in the formula, L is the body length of the AGV.
Further, the controlling the AGV to converge to a desired pose by designing an inversion sliding mode controller includes:
according to the position error tracking model of the current position and the expected position of the AGV, the transverse displacement error e of the actual position and the expected position is calculated x Longitudinal displacement error e y And course angle error e θ Design of slip form surface S 1 、S 2 、S 3 ：
Wherein, c 1 、c 2 、c 3 Are all constant and c 1 ＞0，c 2 ＞0，c 3 ＞0；
The sliding mode approach law is as follows:
wherein, alpha is more than 1, epsilon is more than 0, k is more than 0, i is not less than 1,2,3;
and (3) obtaining a state equation of the pose error between the actual pose and the expected pose of the AGV according to equations (12) and (16):
and (3) designing a system control input Q = (u 1, u 2), converting the path tracking problem of the AGV into control over the advancing speed v of the AGV and the steering angle delta of the single steering wheel, and enabling the position and attitude error of the AGV to quickly approach zero.
Further, the control input Q is obtained according to the following steps:
Q＝TQ r -V (18)
T＝[cosθ e 0；0 1] T
V＝[v 1 v 2 ] T
wherein H is a gain matrix;
the forward speed and angular velocity of the AGV are calculated according to equation (18):
in the formula, ω r A desired steering angular velocity for the AGV;
obtaining control input according to the calculated forward speed and angular speed of the AGV and the self-kinematics model of the AGV:
in a second aspect, an automatic navigation control device for an AGV includes: a laser radar sensor, an incremental encoder and a controller,
the laser radar sensor is used for measuring AGV positioning data and sending the measured positioning data to the controller;
the incremental encoder is used for measuring AGV positioning data in an interval period of two adjacent scanning times of the laser radar sensor and sending the measured positioning data to the controller;
the controller is used for executing the automatic navigation control method.
Further, the automatic navigation control device for AGV further comprises: the safety protection module is used for acquiring an obstacle avoidance sensor signal and/or an emergency stop protection signal and sending the obstacle avoidance sensor signal and/or the emergency stop protection signal to the controller, and the controller controls the driving motor and/or the steering motor to execute corresponding actions according to the received obstacle avoidance sensor signal and/or the emergency stop protection signal.
Furthermore, the safety protection module is also used for acquiring a limiting protection signal and sending the limiting protection signal to the controller, and the controller controls the lifting motor to execute corresponding actions according to the received limiting protection signal.
In a third aspect, an automatic navigation control device for an AGV includes a processor and a storage medium;
the storage medium is to store instructions;
the processor is used for operating according to the instruction to execute the steps of the automatic navigation control method of the AGV.
In a fourth aspect, a computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the aforementioned automatic navigation control method for an AGV.
Compared with the prior art, the invention has the following beneficial technical effects:
1) The positioning data is acquired by adopting two positioning sensors, namely the laser radar sensor and the incremental encoder, the installation cost is low, the path is convenient to change, the incremental encoder can make up the defect of small running frequency of the laser radar sensor, and the stability and reliability of positioning can be improved by adopting the combination positioning of the two sensors;
2) By carrying out data filtering and data fusion on the data of the laser radar sensor and the data of the incremental encoder, the finally obtained coordinate value is returned to the main controller for navigation control, so that the problems of inaccurate positioning, data loss and the like caused by independently adopting one sensor are mutually compensated, higher positioning precision can be obtained, and the stability of the positioning data and the reliability of the positioning data in the operation process of the AGV are ensured;
3) The improved sliding mode control method is adopted to track the path of the AGV, can quickly realize the driving control of the AGV, has the advantages of strong anti-interference capability, quick response, good self-adaption and the like, is not influenced by parameter change, and improves the tracking stability and the tracking precision.
Drawings
FIG. 1 is a flow chart of a method for automatic navigation control of an AGV according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of laser radar sensor data and incremental encoder data fusion;
FIG. 3 is a plot of lidar sensor data versus incremental encoder scan period;
FIG. 4 is a simplified model of a fork lift AGV;
FIG. 5 is a diagram of a global coordinate coeffi-cient model of a fork lift AGV;
fig. 6 is a diagram of an inversion sliding mode control structure provided in an embodiment of the present invention;
FIG. 7 is a block diagram of an AGV auto-navigation control apparatus according to an embodiment of the present invention;
FIG. 8 is a block diagram of an automatic navigation control device for an AGV according to another embodiment of the present invention;
fig. 9 is a detailed block diagram of the automatic navigation control apparatus of fig. 8.
Detailed Description
The invention is further described with reference to specific examples. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
Example 1
As shown in fig. 1, an automatic navigation control method for an AGV includes:
the method comprises the following steps that S1, AGV positioning data measured by a laser radar sensor and AGV positioning data measured by an incremental encoder in an interval period of two adjacent scanning of the laser radar sensor are received;
adopt laser radar sensor to acquire AGV's positioning data alone, because laser radar sensor's operating frequency is little, can lead to AGV positioning error in the operation process, when obtaining the positioning data after laser radar scanning a cycle promptly, AGV has passed through the scanning of several times in the calculation cycle of procedure, so when AGV moves, there is the distance difference at the distance that the distance of motion will be after the scanning of laser radar operation in a cycle, lead to the positioning data inaccurate, and adopt a sensor alone still to appear the positioning data easily and lose the scheduling problem.
In the embodiment of the invention, two sensors, namely the laser radar sensor and the incremental encoder, are adopted for combined positioning, AGV positioning data measured by the laser radar sensor is used as main positioning navigation data of the AGV, the incremental encoder is used for measuring the AGV positioning data in an interval period of two adjacent scanning times of the laser radar, and the stability and the reliability of positioning can be improved by adopting the two sensors for combined positioning.
S2, respectively filtering the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder, and fusing the two kinds of filtered data to obtain a final AGV position coordinate;
because the data information transmitted by the laser radar sensor and the incremental encoder can be interfered by electric signals and electromagnetic environment, in order to ensure the stability of data and the reliability of the data in the operation of the AGV, data filtering and data fusion are firstly carried out on the data of the laser radar sensor and the data of the incremental encoder, and the stability and the reliability of output data are ensured.
The data filtering may use a method of combining an S filter and a G filter, i.e., an S-G filter. Data filtering is respectively carried out on the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder through the S-G filter, and the method specifically comprises the following steps:
selecting the length of a filtering window, then carrying out least square polynomial fitting on data in the window, obtaining a central curve of the data through fitting, taking the central curve as filtering output, and finally carrying out smoothing processing on all the data through iterative computation.
As mentioned above, when the fork truck type AGV moves, the movement distance in one period is different from the scanned distance of the laser radar operation, and the problem is solved by data fusion.
As shown in fig. 2, in the data fusion, feedback data of the laser radar is used as main positioning navigation data of the AGV, and in an interval period between two adjacent scans of the laser radar, an incremental encoder is used for dead reckoning, and then the dead reckoning is overlapped with data of the laser radar, so that the calculation of a positioning coordinate is realized, finally obtained coordinate values are returned to a controller for navigation control, and two sensors are used for combined positioning, so that the two sensors can compensate each other to obtain higher positioning accuracy.
FIG. 3 is a graph of lidar sensor data and incremental encoder scan period. In order to realize the time difference due to the difference in frequency, the relationship of the positioning coordinates may be calculated by the periodic variation as shown in fig. 3. The scanning frequency of the laser radar is lower than the running frequency of the incremental encoder and the main program, and at t 0 The time, the feedback position coordinate of the laser radar is (x) 0 ，y 0 ) Since the period of the lidar is slow, the lidar is at t 0 To t 2 The position coordinates of the time are all (x) 0 ，y 0 ) And the forklift AGV is moving during this period of time, so when this receives the change value of the laser radar, the forklift AGV has moved a short distance, which can be calculated by the incremental encoder according to the following formula:
agv_x＝x 0 +v encoder for encoding a video signal cosδ(t 2 -t 1 )
agv_y＝y 0 +v Encoder for encoding a video signal sinδ(t 2 -t 1 ) (1)
In the formula, (agv _ x, agv _ y) represents two kinds of constantsPosition coordinates (x) of AGV obtained after bit data fusion 0 ，y 0 ) AGV for lidar sensor feedback at t 0 Position coordinates of time of day, v Encoder for encoding a video signal The forward speed of the AGV fed back by the incremental encoder is delta, which represents the steering angle of the single steering wheel of the AGV, and t 1 、t 2 Respectively corresponding time moments of adjacent two-time scanning of the laser radar sensor.
According to the positioning algorithm of the forklift AGV, the navigation positioning precision is more accurate by combining the acquired laser radar data and the encoder data with a fusion algorithm, the motion data of the encoder is continuously superposed on the basis of the laser radar, and the authenticity of the data is higher. The feedback period of the laser radar is long, the period of the encoder is short, the measured real distance has errors with actual radar data, the data finally obtained after the two kinds of data are fused is higher than the authenticity of the data value measured by the radar independently, the data adopting a complementary fusion algorithm is more accurate through result analysis, and the obtained data are laid in an early stage for improving the tracking precision.
And S3, establishing a pose error tracking model of the current pose and the expected pose of the AGV through AGV kinematics modeling, designing a sliding mode surface according to the pose error tracking model, adding an approach law to obtain control output of a sliding mode controller, controlling a driving motor and a steering motor to execute corresponding actions according to the control output to enable the AGV to approach the expected pose, and controlling the AGV to converge to the expected pose through designing an inversion sliding mode controller.
Before tracking the path of the AGV, path planning is carried out on the AGV. Path planning is used to plan the shortest path during the operation of the AGV. The method specifically comprises the following steps:
ss1: modeling an AGV operation environment;
specifically, a grid method can be used for modeling the AGV running environment; and cutting the working environment of the mobile robot into grids which have the same size and are connected with each other, wherein each grid corresponds to corresponding position information.
ss2: setting an AGV starting point and reaching a preset target point;
specifically, the departure point and the arrival at the predetermined target point of one or more AGVs may be set at the same time.
ss3: acquiring a path with optimal or suboptimal distance by combining with the real-time running condition of the AGV;
an optimal path is searched for from the starting point to a single target point, and a global path is planned. The particle swarm optimization and the optimal target priority search method can be combined to preferentially plan the path of the target point with the lowest selection cost, and the particle swarm optimization sequentially and preferentially plans the path of the target point with the lowest subsequent selection cost in the same way to obtain the path with the optimal or suboptimal distance, reduce the redundant points of the path and shorten the path length.
When a fault occurs in the AGV or a new obstacle occurs in the planned path, dynamic adjustment may be performed using the particle swarm algorithm, using the latest value of the control parameter that is iteratively updated in the particle swarm algorithm.
ss4: and optimizing the obtained path with the optimal or suboptimal distance to obtain the optimal path.
Specifically, the optimal path is inverted by feedback.
Then, path tracking is performed on the AGV, which specifically includes:
step S31, establishing a mathematical model of the AGV system;
matching a space map scanned by the laser radar with a map in a working condition environment, then establishing local coordinates by taking the AGV as an original point of a coordinate system, and realizing the calculation of the steering angle and the control quantity of the AGV self course angle through the space conversion between the local coordinates and the global coordinates.
FIG. 4 is a simplified model of a fork lift AGV, L representing the distance of the single steering wheel from the center axis of the left and right driven wheels; d represents the shaft spacing between the left and right driven wheels.
Fig. 5 is a model diagram of a global coordinate coefficient mathematical model of a forklift AGV, where a coordinate system XOY is a global coordinate system, and since a laser radar system can establish the coordinate system for a working condition environment, the coordinate system can be divided into a local coordinate and a global coordinate. For convenience of calculation, a space map scanned by the laser radar is matched with a map in a working condition environment, then a local coordinate is established by taking the forklift type AGV as an origin of a coordinate system, and calculation of the steering angle and the control quantity of the heading angle of the AGV is achieved through space conversion between the local coordinate and the global coordinate.
As shown in fig. 5, the coordinate system XOY matches the working condition environment during the map construction process, so the global coordinate system is the plant map coordinate system. The local coordinate system is established by taking the middle point of the central axis of the left driven wheel and the right driven wheel of the AGV as the origin, taking the central axis direction of the driven wheel as the longitudinal axis and taking the direction perpendicular to the central axis as the transverse axis, and the local coordinate system established by the local coordinate system is X ' O ' Y ', meanwhile, the steering angle of the single steering wheel is delta, the heading angle of the AGV is theta, the advancing speed of the single steering wheel is v, and Y is r Is the expected trajectory of the AGV in the global coordinate system. The origin O' of the local coordinates has a coordinate point (x) in the global coordinate system a ，y a )，x e And y e Respectively are the tracking errors of the front and back states of the AGV path.
From the mathematical model shown in FIG. 5, the kinematic equation for the AGV can be found as:
in the formula, ω represents the steering angular velocity of the AGV.
Because the position of the laser radar point has a distance difference with the origin position of the local coordinate system, in order to facilitate the calculation of the tracking algorithm, the local coordinate system is spatially converted into the coordinate position of the central axis of the left and right driven wheels of the forklift type AGV at the global coordinate, so the coordinate of the origin position of the local coordinate at the global coordinate system is formula (3), and is also a moving point in the path tracking process:
wherein, (x-L, y and theta) are the origin positions of local coordinates; (x) a 、y a And θ) are coordinates of the local coordinate origin position in the global coordinate system.
The kinematic equation for an AGV is:
step S32, designing sliding mode surface parameters;
first, a model of the attitude error is built, as shown in FIG. 5, the current attitude of the AGV is p (x) in the global coordinate system XOY a ，y a θ), the expected pose is p r (x r ，y r ，θ r ) And if so, the position and posture error tracking model of the current posture and the expected posture of the AGV is as follows:
in the formula (I), the compound is shown in the specification,
are each x e 、y e 、θ e Derivative with respect to time, x e 、y e 、θ e Respectively a transverse displacement error, a longitudinal displacement error and a course angle deviation under an XOY coordinate system,
are respectively x r 、y r 、θ r Derivative with respect to time, where x r 、y r Expected coordinate values, theta, of the AGV on the X-axis and Y-axis, respectively r Is the desired heading angle of the AGV.
The control variables of the AGV comprise a transverse displacement error, a longitudinal displacement error and a course angle deviation, the control of a driving motor and a steering motor can be realized according to sliding mode control, and path tracking can be realized through the design of a sliding mode surface and the establishment of a kinematics model of the AGV.
Then, a sliding mode surface is established, sliding mode control is respectively carried out on the transverse displacement error and the longitudinal displacement error, and the sliding mode surfaces are S respectively 1 And S 2 ：
In the formula, c 1 、c 2 The parameters of the integral sliding mode surface are all constants;
the path tracking algorithm adopts a sliding mode control and inversion method and a combined algorithm, different approach laws are mainly designed for the sliding mode control to realize that the moving point quickly reaches a stable state, the approach laws have important influence on the system moving to a balance point, and the problem of jitter for achieving the sliding mode control is solved. The approach rate designed by the invention is as follows:
in the formula, k 1 、k 2 Is the coefficient of the designed approach rate.
By substituting the expressions (6) and (7) into the expression (5), the desired course angle θ of the AVG can be calculated r ：
Carrying out sliding mode control calculation on the course angle according to a mode of carrying out sliding mode solving on the transverse and longitudinal displacement errors, and designing a sliding mode surface S 3 ：
S 3 ＝θ e +c 3 ∫θ e (9)
Approximation law of sliding mode
In the formula, c 3 、k 3 And epsilon is the coefficient of the designed slip form surface and the approach rate.
And (5) integrating the formulas (5) to (10) to obtain a control output u of the sliding mode controller:
wherein the parameter settings are as shown in table 1:
TABLE 1 parameter settings
And S33, designing an inversion sliding mode controller for verification.
Fig. 6 is a diagram of an inverse sliding mode control structure according to an embodiment of the present invention, which is based on an AGV mathematical model, and designs a switching function of a sliding mode surface according to sliding mode control, and then designs a control variable according to stability based on a Lyapunove function in an inversion method, and implements path tracking by the control variable.
Specifically, first, the actual pose p (x, y, θ) and the expected pose p of the AGV are taken r (x r ，y r ，θ r ) The error of the model is used as the input of a controller, a sliding mode surface switching function of the model is designed, and the designed transverse displacement error, longitudinal displacement error and course angle error sliding mode surfaces are shown as the following formulas:
wherein, c 1 、c 2 、c 3 Are all constant and c 1 ＞0，c 2 ＞0，c 3 ＞0；e x 、e y 、e θ The horizontal displacement error, the longitudinal displacement error and the course angle error of the actual pose and the expected pose are respectively.
The invention designs an approximation law by utilizing a power approximation law and an inverse hyperbolic sine function, the common approximation law is a common method in the sliding mode control process, but the problems of jitter, low tracking precision and the like still exist when the method is applied to path tracking of a forklift AGV, so that innovation and improvement are carried out on the basis of the original approximation law, the novel approximation law mainly comprising the power approximation law and the inverse hyperbolic sine function is adopted, and the stability and the tracking precision of tracking can be improved through the control algorithm.
The nonlinear function can be obtained by utilizing the power approximation law and the inverse hyperbolic sine function design:
wherein: alpha is more than 1.
Designing a sliding mode approach rate:
wherein: arsh(s) is an inverse hyperbolic sine function, epsilon is more than 0, and k is more than 0.
The following can be obtained:
obtaining a related formula of the transverse direction, the longitudinal direction and the course angle of the system according to the designed sliding mode approach rate:
wherein i =1,2,3.
The actual position p (x, y, theta) and the expected position p of AGV are obtained from the equations (12) and (16) r (x r ，y r ，θ r ) The state equation of the pose error:
then by controlling the input Q = [ vm =]Controlling the speed v and the steering angle deltaAnd (5) preparing. For the convenience of controller design, let the control input (u) 1 ，u 2 ) Denoted (v, δ), the specific implementation is as follows:
Q＝TQ r -V (18)
wherein, the first and the second end of the pipe are connected with each other,
T＝[cosθe 0；0 1] T
V＝[v 1 v 2 ] T
in the formula, H is a gain matrix.
The forward speed and angular velocity of the AGV are calculated according to equation (18):
in the formula, omega r A desired steering angular velocity for the AGV;
obtaining control input according to the calculated forward speed and angular speed of the AGV and a kinematics model of the AGV:
the control input Q is a main parameter for controlling and tracking the steering wheel of the AGV, so the main control mode of the control input Q is to calculate the speed and the angular velocity of the AGV and then calculate the control quantity for controlling the steering wheel of the AGV according to a mathematical model, namely (u) 1 ，u 2 ) Thereby realizing the aim of path tracking. By designing an inversion sliding mode controller for verification, the accuracy in the path tracking control process is improved more directly and more effectively, and the convergence of the AGV system is accelerated.
Example 2
As shown in fig. 7, an automatic navigation control device for an AGV includes: lidar sensor 701, incremental encoder 702, and controller 703.
And the laser radar sensor 701 is configured to measure AGV positioning data and send the measured positioning data to the controller 703.
The incremental encoder 702 is configured to measure AGV positioning data in an interval period between two adjacent scans of the laser radar sensor 701 and send the measured positioning data to the controller 703;
a controller 703 is configured to execute the automatic navigation control method of an AGV according to embodiment 1.
As shown in fig. 7, the apparatus further includes a safety protection module 704, where the safety protection module 704 is configured to obtain an obstacle avoidance sensor signal and/or an emergency stop protection signal and send the obstacle avoidance sensor signal and/or the emergency stop protection signal to the controller 703, and the controller 703 controls the driving motor 705 and/or the steering motor 706 to perform corresponding actions according to the received obstacle avoidance sensor signal and/or the emergency stop protection signal.
The safety protection module 704 is further configured to obtain a limit protection signal and send the limit protection signal to the controller 703, and the controller 703 controls the lifting motor 707 to execute a corresponding action according to the received limit protection signal.
Example 3
Fig. 8 is a structural diagram of an automatic navigation control device of an AGV according to an embodiment of the present invention, which is applicable to a situation that the AGV operates autonomously according to navigation information in a storage environment, and can be implemented in a software and hardware manner, as shown in fig. 8, the automatic navigation control device includes: the device comprises a core control layer, a drive control layer and an information processing layer.
The core control layer is used for control decision and operation processing of the AGV control system;
the information processing layer is used for applying the AGV on the software level and is used for acquiring and processing information in the running process of the AGV;
the driving control layer is used for realizing AGV motion control, and the driving control layer is through receiving driving control signal, and then realizes the control of driving control layer to driving motor, steering motor and lifting motor.
As shown in fig. 9, the core control layer includes an embedded controller, and the embedded controller is used for operating programs and processing input/output control variables, and performs functions of processing control data and converting input/output data.
The core control layer takes an embedded controller as main hardware support. The main components of the core control layer include embedded controller, I/O port, RJ45, DVI, USB and other interfaces. The core control layer is connected with the external navigation positioning module, the communication module, the safety protection module, the man-machine interaction module, the driving control module, the lifting control module and the power supply module, so that the operation is processed through a control algorithm in the local area network. Navigation orientation module connects through RJ45 and Ethernet, and communication module then realizes the communication through Ethernet RJ45 interface and connects, and human-computer interaction module then realizes the transmission of data through DVI, and drive control module and lift control module realize control through the CAN bus, thereby safety protection module is then the IO port connection through the controller realizes safety protection's function.
With continued reference to fig. 9, the information processing layer includes a navigation positioning module, a security protection module, a communication module, and a human-computer interaction module.
The navigation positioning module at least comprises two positioning sensors, and can acquire the coordinate position of the AGV and make motion guidance for navigation motion by adopting a laser navigation mode.
The safety protection module is used for acquiring and processing information of devices such as an obstacle avoidance sensor, emergency stop protection and limit protection and the like, and is used for improving the safety of the AGV in the running process.
The communication module is used for carrying out local communication among a plurality of devices to realize the transmission of communication data.
The human-computer interaction module is used for processing the setting of the basic information of the AGV and realizing the connection between users and equipment.
The information processing layer is applied to the software layer of the AGV and mainly used for processing information of the navigation positioning module, the safety protection module, the communication module and the human-computer interaction module.
Navigation orientation module can adopt laser radar sensor and incremental encoder to satisfy navigation orientation's requirement, and laser radar passes through the reflection location of laser board and the laser emission scanning of self, confirms position coordinate, and the incremental encoder is for remedying laser radar sensor's the not enough that operating frequency is little to calculate AGV drive distance with this. The operating frequency of the incremental encoder used must meet the operating requirements of the AGV in order to better obtain the coordinate information.
The safety protection module adopts protection modes such as an obstacle avoidance sensor, emergency stop protection, limit protection and the like, and processed information includes feedback of the obstacle avoidance sensor to external data, feedback of an emergency stop button and data output of the limit sensor.
The communication module adopts an industrial wireless communication connector, so that not only can the connection of a single device be realized, but also local communication among a plurality of devices can be realized, and the main processed data is the transmission among communication data.
The information data processed by the human-computer interaction module is the setting of the basic information of the AGV, and the connection between the user and the equipment can be realized in the process of realizing the mode conversion.
With continued reference to FIG. 9, the drive control layer is used to implement motion control for the AGV. Specifically, the driving control layer mainly controls the driving motor, the steering motor and the lifting motor through receiving the driving control signal by the driving controller, and mainly comprises a driving control module, a lifting control module, a driving motor, a steering motor, a lifting motor, a connection data line, an interface and other basic components. The data exchange and control mode of the driving control layer is based on a CAN bus to realize the control process, the real-time control of the motor and the system is realized by receiving and sending message data, the sent message is the control quantity obtained by a control algorithm, and then the control quantity is converted into the message data, so that the control is realized, the problems of the matching and the data association between the driving motor and the steering motor are solved, and the integrity and the stability of the driving control layer are ensured.
The core control layer is used for control decision and operation processing of the AGV control system, data of the navigation positioning module, the communication module and the safety protection module are input, and then the data are output to the human-computer interaction module, the driving control module and the like, so that the functions of the control system are realized, the core control layer is high in computing capacity, multiple in input and output modules and integrated, and rich in external ports, and the data can be conveniently processed through the core control layer; the information processing layer is used for the AGV on the software level, is used for acquiring and processing information in the running process of the AGV, and can accurately acquire data and feed the data back to the core control layer; wherein, navigation positioning module includes two kinds of positioning sensor at least, adopts the laser radar sensor, and installation cost is low, and the route change is convenient, adopts incremental encoder can compensate the not enough that the operating frequency of laser radar sensor is little, and two kinds of at least positioning sensor can improve the stability and the reliability of location.
In another embodiment, an automatic navigation control device for an AGV includes a processor and a storage medium;
a storage medium to store instructions;
the processor is configured to operate according to the stored instructions to perform the steps of the method for automatic navigation control of an AGV of embodiment 1.
In another embodiment, a computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the automatic navigation control method of an AGV of embodiment 1.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. An automatic navigation control method for an AGV is characterized by comprising the following steps:
receiving AGV positioning data measured by a laser radar sensor and AGV positioning data measured by an incremental encoder in an interval period of two adjacent scans of the laser radar sensor;
filtering the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder respectively, and fusing the two kinds of filtered data to obtain a final AGV position coordinate;
establishing a pose error tracking model of the current pose and the expected pose of the AGV, designing a sliding mode surface according to the pose error tracking model, adding an approach law to obtain control output of a sliding mode controller, controlling a driving motor and a steering motor to execute corresponding actions according to the control output so that the AGV approaches the expected pose, and controlling the AGV to converge to the expected pose by designing an inversion sliding mode controller.
2. The method of claim 1, wherein said filtering the positioning data measured by the lidar sensor and the incremental encoder comprises:
selecting the length of a filtering window, performing least square polynomial fitting on data in the window to obtain a central curve of the data, and smoothing the central curve.
3. The AGV auto-navigation control method according to claim 1, wherein the fusing of the two filtered data includes:
if the AGV position coordinates obtained by the laser radar sensor in the interval period of the two adjacent scanning processes are the same, the positioning data measured by the laser radar sensor and the positioning data measured by the incremental encoder in the interval period of the two adjacent scanning processes of the laser radar sensor are fused according to the following formula, and the final AGV position coordinates are obtained:
agv_x＝x 0 +v encoder for encoding a video signal coSδ(t 2 -t 1 )
agv_y＝y 0 +v Encoder for encoding a video signal sinδ(t 2 -t 1 ) (1)
In the formula, (AGV _ x, AGV _) represents the position coordinates of the AGV obtained by fusing two types of positioning data, (x) 0 ，y 0 ) AGV for lidar sensor feedback at t 0 Position coordinates of time of day, v Encoder for encoding a video signal The forward speed of the AGV fed back by the incremental encoder is delta, which represents the steering angle of the single steering wheel of the AGV, and t 1 、t 2 Respectively corresponding time when the laser radar sensor scans for two adjacent times.
4. The automatic navigation control method of an AGV according to claim 1, wherein the position error tracking models of the current position and the expected position of the AGV are:
in the formula (I), the compound is shown in the specification,
are each x e 、y e 、θ e Derivative with respect to time, x e 、y e 、θ e Respectively a transverse displacement error, a longitudinal displacement error and a course angle deviation under an XOY coordinate system, v is the advancing speed of the single steering wheel of the AGV, delta is the steering angle of the single steering wheel, theta is the course angle of the AGV,
are each x r 、y r 、θ r Derivative with respect to time, (x) r 、y r 、θ r ) Expected pose for AGV, where x r 、y r Expected coordinate values of AGV on X-axis and Y-axis, θ r Is the expected heading angle of the AGV;
designing a sliding mode surface according to the pose error tracking model and adding an approach law to obtain the control output of the sliding mode controller, wherein the control output comprises the following steps:
slip form surface S is respectively designed for transverse displacement error and longitudinal displacement error 1 、S 2 ：
In the formula, c 1 、c 2 Parameters of an integral sliding mode surface;
the designed approach rate is:
in the formula, k 1 、k 2 A coefficient for the designed approach rate;
substituting (6) and (7) into (5) to calculate AVG expected course angle theta r ：
Designing a slip form surface S for course angle deviation 3 ：
S 3 ＝θ e +c 3 ∫θ e (9)
Law of approach
In the formula, c 3 、k 3 Epsilon is a coefficient of a designed sliding mode surface and an approach rate;
and (5) integrating the formulas (5) to (10) to obtain a control output u of the sliding mode controller:
in the formula, L is the body length of the AGV.
5. The automatic navigation control method for the AGV of claim 4, wherein said controlling the AGV to converge to a desired pose by designing an inverse sliding mode controller comprises:
according to the position error tracking model of the current position and the expected position of the AGV, the transverse displacement error e of the actual position and the expected position is calculated x Longitudinal displacement error e y And course angle error e θ Design of slip form surface S 1 、S 2 、S 3 ：
Wherein, c 1 、c 2 、c 3 Are all constant and c 1 >0，c 2 >0，c 3 >0；
The sliding mode approximation law is as follows:
wherein α >1, ε >0, k > -0, i =1,2,3;
and (3) obtaining a state equation of the pose error between the actual pose and the expected pose of the AGV according to equations (12) and (16):
and (3) designing a system control input Q = (u 1, u 2), converting the path tracking problem of the AGV into control over the advancing speed v of the AGV and the steering angle delta of the single steering wheel, and enabling the position and attitude error of the AGV to quickly approach zero.
6. An AGV automatic navigation control method according to claim 5 wherein said control input Q is obtained according to the steps of:
Q＝TQ r -V (18)
T＝[cosθ e 0；0 1] T
V＝[v 1 v 2 ] T
wherein H is a gain matrix;
the forward speed and angular velocity of the AGV are calculated according to equation (18):
in the formula, omega r A desired steering angular velocity for the AGV;
obtaining control input according to the calculated forward speed and angular speed of the AGV and the self-kinematics model of the AGV:
7. an automatic navigation control apparatus for an AGV, comprising: a laser radar sensor, an incremental encoder and a controller,
the laser radar sensor is used for measuring AGV positioning data and sending the measured positioning data to the controller;
the incremental encoder is used for measuring AGV positioning data in an interval period of two adjacent scanning times of the laser radar sensor and sending the measured positioning data to the controller;
the controller is configured to execute the automatic navigation control method of any one of claims 1-6.
8. The automatic navigation control of an AGV of claim 7, further comprising: the safety protection module is used for acquiring an obstacle avoidance sensor signal and/or an emergency stop protection signal and sending the obstacle avoidance sensor signal and/or the emergency stop protection signal to the controller, and the controller controls the driving motor and/or the steering motor to execute corresponding actions according to the received obstacle avoidance sensor signal and/or the emergency stop protection signal.
9. The automatic navigation control device of an AGV of claim 8, wherein the safety protection module is further configured to obtain a limit protection signal and send the limit protection signal to the controller, and the controller controls the lift motor to perform a corresponding action according to the received limit protection signal.
10. The automatic navigation control device of the AGV is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of claims 1 to 6.
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