CN115979249B - Navigation method and device of inspection robot - Google Patents
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Abstract
The invention relates to the technical field of autonomous navigation, and discloses a navigation method of a patrol robot, which comprises the following steps: the method comprises the steps of constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology, acquiring an optional routing set of the routing inspection robot based on the global map and a target position, selecting an energy consumption optimal routing from the optional routing set to the target position based on an optimization function and an energy consumption calculation model, acquiring pose information of the routing inspection robot during autonomous routing inspection, calculating a yaw angle based on the pose information of the routing inspection robot and the energy consumption optimal routing, and driving the routing inspection robot to finish navigation based on the pose information of the routing inspection robot and the yaw angle. The invention also provides a navigation device of the inspection robot, electronic equipment and a computer readable storage medium. The invention can solve the problems of the inspection robot that the inspection robot depends on a fixed track, and has poor flexibility, high inspection cost and poor navigation positioning precision.
Description
Technical Field
The present invention relates to the field of autonomous navigation technologies, and in particular, to a navigation method and apparatus for a patrol robot, an electronic device, and a computer readable storage medium.
Background
The inspection robot is a robot for replacing manual inspection and maintenance of equipment and field environment, can automatically inspect to detect the states of field equipment, temperature, humidity, liquid level and the like, and once a problem is found, an alarm is sent out in time, so that enterprises are helped to ensure the safety of the equipment and the field environment, and the production efficiency is improved.
The current mainstream navigation method of the inspection robot is track navigation, namely the inspection robot executes the inspection task through a plurality of pre-paved fixed tracks, the navigation principle is simple and the reliability is high, but the track paving is complex, the line changing or increasing and decreasing is troublesome, so that the inspection robot only depends on a plurality of fixed tracks, the flexibility is poor, and the inspection cost is high. In addition, the inspection robot is commonly used for navigation positioning by a wheel type odometer and an inertial measurement unit, but serious accumulated errors can be generated after long-time use, and the dead reckoning deviation of the robot is easily caused to be overlarge, so that the inspection robot deviates from a preset inspection route, and the inspection task fails.
Disclosure of Invention
The invention provides a navigation method, a navigation device and a computer readable storage medium of a patrol robot, and mainly aims to solve the problems that the patrol robot depends on a fixed track, and has poor flexibility, high patrol cost and poor navigation positioning precision.
In order to achieve the above object, the navigation method of the inspection robot provided by the present invention includes:
receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein a hardware platform of the inspection robot consists of a depth camera, a main control unit and a robot chassis;
constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology;
acquiring an optional inspection route set of the inspection robot based on the global map and the target position, and constructing an optimization function of the optional inspection route set and the travelling speed of the inspection robot;
acquiring a relation model of motor voltage and battery voltage of the inspection robot, and constructing an energy loss calculation model of the inspection robot based on the relation model, wherein the energy loss calculation model comprises the length of an optional inspection route set;
based on the optimization function and the energy consumption calculation model, selecting an energy consumption optimal inspection route from the selectable inspection route set to the target position;
the method comprises the steps of obtaining a local map at an actual position by using a patrol robot, converting the local map into a global map based on an optimal value of a pre-constructed coordinate transformation parameter to be matched, and obtaining pose information of the patrol robot during autonomous patrol, wherein coordinates of the patrol robot mapped to the global map according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z]Representing coordinates of the inspection robot i in the local map,t=[t x ，t y ，t z ]representing the translation of inspection robot i in the x, y, z directions [r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s= sin/>
，c=cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis;
calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
and driving the inspection robot to complete navigation based on the pose information and the yaw angle of the inspection robot.
Optionally, the depth camera used by the inspection robot is an ASTRA depth camera, and the camera is arranged on the top of the robot;
the robot chassis consists of a control chip, a battery, a servo driver, a motor and wheels.
Optionally, the constructing the global map of the surrounding environment by using the pre-constructed visual SLAM technology includes:
receiving a depth camera image;
based on a pre-constructed Graph-SLAM algorithm, outputting a 3D point cloud image according to a depth camera image, and establishing a world coordinate system in the 3D point cloud image;
and integrating the 3D point cloud image in the world coordinate system based on a pre-constructed coordinate conversion method to obtain a global map.
Optionally, the constructing an optimization function of the optional inspection route set and the inspection robot running speed includes:
performing segmentation on the selectable routing set based on the target position to obtain a plurality of groups of segmented routing sets;
receiving an optimized adjustment factor of the inspection route and the inspection robot;
acquiring the number of inspection robots running on an inspection route;
calculating the crowdedness of the inspection route based on the number of the inspection robots;
calculating an optimization function of the running speed of each segment inspection route and the inspection robot in each group of segment inspection route set based on the optimization adjustment factors and the crowdedness degree:
wherein ,
indicating that the inspection robot is driving at +.>
The +.f. of the alternative route>
The speed of travel of the individual section of the route, +.>
Indicating the initial running speed of the inspection robot, < + >>
Indicate->
Optimal adjustment factors of individual sectional inspection routes and inspection robots, < >>
Indicating the +.f in the selectable tour route set>
The +.f. of the alternative route>
Congestion degree of each segment inspection route.
Optionally, the acquiring a relation model of the voltage of the motor and the voltage of the battery of the inspection robot includes:
receiving the duty ratio of a patrol robot battery by adopting a PWM technology, the internal resistance of a motor, the counter electromotive force coefficient of the motor, the reduction ratio of a motor speed reducer, the rotating speed of the motor and the working current of the motor;
Based on the duty ratio of the battery adopting the PWM technology, the internal resistance of the motor, the counter electromotive force coefficient of the motor, the reduction ratio of a motor speed reducer, the motor rotating speed and the motor working current, a relation model of the motor voltage and the battery voltage of the inspection robot is constructed as shown in the following formula:
wherein ,
represents the motor voltage>
Represents battery voltage, < >>
Indicating the duty cycle of the battery using PWM technique, +.>
Representing the motor current of the motor when in operation, +.>
Is the internal resistance of the motor>
For the back emf coefficient of the motor>
Is the speed reduction ratio of the motor speed reducer, +.>
Indicated at motor current +.>
The motor speed in the case is determined.
Optionally, the constructing an energy loss calculation model of the inspection robot based on the relation model includes:
acquiring the inspection robot at the first positioniSelectable tour routejRoute length of each sectional inspection route;
according to the route length, constructing an energy loss calculation model of the inspection robot as shown in the following formula:
wherein ,
represents the energy consumption value of the inspection robot, < ->
Indicate->
The selectable tour route +.>
Route length of each segment inspection route.
Optionally, the converting the local map to the global map based on the optimal value of the pre-constructed coordinate transformation parameter for matching includes:
Obtaining an odometer reading;
acquiring initial coordinate transformation parameters based on the odometer reading;
mapping the point cloud in the local map into the global map based on the initial coordinate transformation parameters, and establishing a probability distribution function of the point cloud, wherein the probability distribution function is shown in the following formula:
wherein ,qis a point cloudxThe position average in the voxel unit,
is the variance of the point cloud;
acquiring the sum of probability distribution of all point clouds according to the probability distribution function;
obtaining a score value of the coordinate transformation parameter based on the sum of all the point cloud probability distributions;
optimizing the fractional value of the coordinate transformation parameter based on a pre-constructed Hessian matrix method to obtain an optimized value, and selecting the maximum value of the optimized value;
and obtaining the optimal value of the coordinate transformation parameter based on the maximum value of the optimal value.
Optionally, the calculating the yaw angle based on the pose information of the inspection robot and the energy consumption optimal inspection route includes:
establishing local navigation target points based on optimal routing inspection routeP(p x ，p y ) The distance between the local target point and the robot is fixed, and the whole course is on the optimal inspection route;
the yaw angle is calculated by:
wherein ,
the yaw angle of the inspection robot is represented, (x, y) represents the coordinates of the inspection robot in a world coordinate system, and the yaw angle of the inspection robot is represented by the x, y p x ，p y ) Representing local navigation target pointsPCoordinates in the world coordinate system.
Optionally, the navigation is completed based on the pose information and the yaw angle of the inspection robot, including:
acquiring PWM signals based on pose information and yaw angle of the inspection robot;
the inspection robot is controlled to perform straight running and steering movement through PWM signals;
when the inspection robot finds an obstacle in the moving process, a pre-constructed dynamic window method is adopted to reconstruct an optional inspection route set, and a new optimal inspection route is obtained to finish navigation.
In order to solve the above problems, the present invention also provides a navigation device of a patrol robot, the device comprising:
the inspection target determining module is used for receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein the inspection robot hardware platform consists of a depth camera, a main control unit and a robot chassis;
the global map and optional routing inspection route construction module is used for constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology and acquiring an optional routing inspection route set of the inspection robot based on the global map and the target position;
The optimal inspection route selection module is used for constructing an optimization function of an optional inspection route set and the running speed of the inspection robot, obtaining a relation model of the motor voltage and the battery voltage of the inspection robot, constructing an energy loss calculation model of the inspection robot based on the relation model, and selecting an energy consumption optimal inspection route from the optional inspection route set to a target position based on the optimization function and the energy loss calculation model;
the position and yaw angle calculation module is used for acquiring a local map at an actual position by using the inspection robot, converting the local map into a global map for matching based on an optimal value of a pre-constructed coordinate transformation parameter to obtain position information of the inspection robot during autonomous inspection, wherein coordinates of the inspection robot mapped to a global map coordinate system according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z]Representing coordinates of the inspection robot i in the local map,t=[t x ，t y ，t z ]representing the translation of inspection robot i in the x, y, z directions [r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s= sin/>
，c=cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis;
Calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
and the navigation module is used for driving the inspection robot to finish navigation based on the pose information and the yaw angle of the inspection robot.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
a memory storing at least one instruction;
and the processor executes the instructions stored in the memory to realize the navigation method of the inspection robot.
In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having stored therein at least one instruction that is executed by a processor in an electronic device to implement the navigation method of the inspection robot described above.
In order to solve the problems in the background technology, a global map of the surrounding environment is firstly constructed by adopting a pre-constructed visual SLAM technology, then an optional routing set of the routing robot is obtained based on the global map and a target position of the routing robot, an optimization function of the optional routing set and the running speed of the routing robot is constructed, a relation model of motor voltage and battery voltage of the routing robot is obtained, an energy loss calculation model of the routing robot is constructed based on the relation model, and an energy consumption optimal routing from the optional routing set to the target position is selected based on the optimization function and the energy loss calculation model. Therefore, the method for constructing the global map does not need to lay fixed tracks in advance, but acquires the routing inspection route set, and finally selects the routing inspection route according to the energy consumption optimal method, so that the flexibility is high, and the routing inspection cost is low. In addition, the local map at the actual position is obtained by the inspection robot, the local map is converted into the global map for matching based on the optimal value of the pre-constructed coordinate transformation parameter, and the pose information of the inspection robot during autonomous inspection is obtained. Therefore, the positioning of the inspection robot is obtained based on the optimal value of the coordinate transformation parameter, and the coordinate transformation parameter obtained by the odometer is optimized, so that the positioning accuracy is improved. Therefore, the navigation method, the navigation device, the electronic equipment and the computer readable storage medium of the inspection robot can solve the problems that the inspection robot depends on a fixed track, and has poor flexibility, low inspection cost and poor navigation positioning accuracy.
Drawings
Fig. 1 is a flow chart of a navigation method of a patrol robot according to an embodiment of the invention;
FIG. 2 is a functional block diagram of a navigation device of a inspection robot according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the navigation method of the inspection robot according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a navigation method of a patrol robot. The execution subject of the navigation method of the inspection robot includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the navigation method of the inspection robot may be performed by software or hardware installed in a terminal device or a server device. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Embodiment one:
referring to fig. 1, a flow chart of a navigation method of a inspection robot according to an embodiment of the invention is shown. In this embodiment, the navigation method of the inspection robot includes:
s1, receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein the inspection robot hardware platform consists of a depth camera, a main control unit and a robot chassis.
In the embodiment of the invention, the starting instruction and the target position of the inspection robot can be integrated to the mobile equipment through the APP or sent out through a remote controller and the like. By way of example, the Xiaoming is taken as a production workshop manager of a factory, and the inspection robot needs to be utilized to sequentially inspect whether production equipment in different positions of the production workshop is normally operated within 6 hours from 11 hours in the daytime to 5 hours in the afternoon, so that a starting instruction of the inspection robot is sent out, and a target position is set.
It should be explained that, in the embodiment of the present invention, the camera used by the inspection robot is an ASTRA depth camera, and the camera is mounted on the top of the robot;
the robot chassis consists of a control chip, a battery, a servo driver, a motor and wheels.
It should be understood that the depth camera used in the embodiment of the present invention has a plurality of cameras, unlike a common camera, which can not only collect color pictures, but also read out the distance between each pixel and the camera. The method is characterized in that the distance between the object and the camera can be calculated by actively emitting light to the object and receiving returned light through infrared structured light.
S2, constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology.
It should be noted that SLAM is an abbreviation of "Simultaneous Localization and Mapping" and is translated into "simultaneous localization and mapping". It refers to a main body carrying a specific sensor, and under the condition of unknown surrounding environment, a model of the surrounding environment is built in the motion process, and the motion of the main body is estimated. In particular, since the sensor employed by the inspection robot in the present embodiment is a depth camera, a visual SLAM technique is employed.
In detail, the method for constructing the global map of the surrounding environment by adopting the pre-constructed visual SLAM technology comprises the following steps:
receiving a depth camera image;
based on a pre-constructed Graph-SLAM algorithm, outputting a 3D point cloud image according to a depth camera image, and establishing a world coordinate system in the 3D point cloud image;
And integrating the 3D point cloud image in the world coordinate system based on a pre-constructed coordinate conversion method to obtain a global map.
S3, acquiring an optional inspection route set of the inspection robot based on the global map and the target position, and constructing an optimization function of the optional inspection route set and the travel speed of the inspection robot.
It is emphasized that the present invention does not rely on pre-paved tracks, but calculates, by the master control unit, an alternative inspection route from the location where the inspection robot is located to the target location, based on a global map of the built surrounding environment, wherein the alternative inspection route may be a plurality of, and there is no obstacle on the whole alternative inspection route, and a new alternative inspection route set should be recalculated when the travel route is suddenly obstructed.
Illustratively, a factory floor manager uses a patrol robot to patrol the equipment in the factory floor from 11 pm to 5 pm for normal operation. Since there may be multiple inspection routes in the production plant, but only 5 inspection routes may be available for inspecting the positions of all the devices in the production plant and for realizing the device detection, the 5 inspection routes are called an optional inspection route set.
In addition, the invention adopts the principle of energy consumption optimization to select the optimal inspection route from the set of the selectable inspection routes, so the standard of selecting the optimal inspection route from the 5 selectable inspection routes is as follows: keeping the energy consumption to a minimum and within the maximum working time (such as 11 hours in the daytime to 5 hours in the afternoon). It should be appreciated that, because one important indicator affecting the amount of energy consumption is the working time, when the route length of each alternative inspection route is determined, the amount of energy required by the inspection robot to complete the inspection task on the alternative inspection route is directly related to the speed of travel. Therefore, an optimization function of each selectable routing inspection route and the running speed is constructed, and the optimal routing inspection route can be selected based on the optimization function.
In detail, the constructing an optimization function of the selectable inspection route set and the inspection robot running speed comprises the following steps:
dividing the selectable inspection route set based on the inspection target position to obtain a plurality of groups of sectional inspection route sets;
receiving an optimized adjustment factor of the inspection route and the inspection robot;
acquiring the number of inspection robots running on an inspection route;
calculating the crowdedness of the inspection route based on the number of the inspection robots;
Calculating an optimization function of the running speed of each segment inspection route and the inspection robot in each group of segment inspection route set based on the optimization adjustment factors and the crowdedness degree:
wherein ,
indicating that the inspection robot is driving at +.>
The +.f. of the alternative route>
The speed of travel of the individual section of the route, +.>
Indicating the initial running speed of the inspection robot, < + >>
Indicate->
Optimal adjustment factors of individual sectional inspection routes and inspection robots, < >>
Indicating the +.f in the selectable tour route set>
Optional patrolFirst stop of route>
Congestion degree of each segment inspection route.
By way of example, the production shop manager uses the inspection robot to inspect whether the equipment in the workshop is operating normally, sets that the starting working point of the inspection robot is the current point of the inspection robot, and the ending working point is the inspection robot parking position of the workshop, and sets a plurality of parking points of equipment A, equipment B, equipment C, equipment D and the like between the current point of the inspection robot and the robot parking position, so that the manager can divide the selectable inspection route set into a plurality of groups of segmented inspection route sets according to the current point of the inspection robot, the equipment A, the equipment B, … and the robot parking position. Namely, each group of sectional inspection route sets comprises a plurality of groups of sectional routes from the current point to the equipment A and a plurality of groups of sectional routes from the equipment A to the equipment B.
S4, acquiring a relation model of motor voltage and battery voltage of the inspection robot, and constructing an energy loss calculation model of the inspection robot based on the relation model, wherein the energy loss calculation model comprises the length of an optional inspection route set.
It is understood that the battery generates electric energy for driving the coil of the motor to rotate so as to drive the inspection robot to move in four-wheel mode, but it is emphasized that the electric energy generated by the battery is not completely converted into the electric energy of the motor, i.e. the motor voltage and the battery voltage have an attenuation relation.
In detail, the obtaining a relation model of the motor voltage and the battery voltage of the inspection robot includes:
receiving duty ratio, motor internal resistance, motor back electromotive force coefficient, reduction ratio of a motor speed reducer, motor rotating speed and motor working current of a patrol robot battery by adopting a PWM technology;
based on the duty ratio of the battery adopting the PWM technology, the internal resistance of the motor, the counter electromotive force coefficient of the motor, the reduction ratio of a motor speed reducer, the motor rotating speed and the motor working current, a relation model of the motor voltage and the battery voltage of the inspection robot is constructed as shown in the following formula:
wherein ,
represents the motor voltage>
Represents battery voltage, < > >
Indicating the duty cycle of the battery using PWM technique, +.>
Representing the motor current of the motor when in operation, +.>
Is the internal resistance of the motor>
For the back emf coefficient of the motor>
Is the speed reduction ratio of the motor speed reducer, +.>
Indicated at motor current +.>
The motor speed in the case is determined.
It should be noted that the pulse width modulation technique (Pulse width modulation, PWM) includes: the phase voltage control PWM, pulse width PWM, random PWM, SPWM, line voltage control PWM and the like are technically characterized in that pulse trains with equal pulse widths are used as PWM waveforms, frequency modulation can be realized by changing the period of the pulse trains, voltage regulation can be realized by changing the duty ratio of the pulses, and the mode can keep the battery voltage constant when the working condition changes, so that the energy consumption calculation of the inspection robot is facilitated. The PWM duty cycle is the ratio of the energization time to the total time in one pulse cycle, for example, a pulse width of 1 μs and a pulse train duty cycle of 4 μs in a signal period of 0.25.
In addition, the counter electromotive force coefficient represents the counter electromotive force generated by the unit rotating speed of the motor under the rated electromagnetic condition, the magnitude of the counter electromotive force coefficient is directly related to the number of winding turns, a magnetic circuit formed by stator and rotor cores, the length of an air gap between the stator and the rotor and the rotating speed of the motor, and is the result generated by the action of an electromagnetic induction law when the motor moves, and the counter electromotive force coefficient has the negative effect of preventing the motor from rotating, so that the embodiment of the invention considers the counter electromotive force coefficient in the calculation of the relation between the battery voltage and the motor voltage.
In addition, the speed reduction ratio of the motor speed reducer is also called as the transmission ratio of the speed reducer, and refers to the ratio of the instantaneous input speed to the output speed in the speed reducer, and the speed reducer mainly has the functions of reducing the rotating speed, increasing the output torque and reducing the inertia of a load. Therefore, when a user sets the maximum working speed of the inspection robot during working, the rotating speed of the motor can be reduced through the speed reducer, so that the inspection robot is ensured not to generate risks due to too wide rotating speed.
Further, the constructing an energy loss calculation model of the inspection robot based on the relation model includes:
acquiring the inspection robot at the first positioniSelectable tour routejRoute length of each sectional inspection route;
according to the route length, constructing an energy loss calculation model of the inspection robot as shown in the following formula:
wherein ,
represents the energy consumption value of the inspection robot, < ->
Indicate->
The selectable tour route +.>
Route length of each segment inspection route.
S5, selecting an energy consumption optimal inspection route from the selectable inspection route set to the target position based on the optimization function and the energy consumption calculation model.
According to the above, the inspection robot energy loss calculation model is:
wherein ,
represents the energy consumption value of the inspection robot, < - >
Indicate->
The selectable tour route +.>
Route length of each segment inspection route.
Thus, the optimized function of the sectional inspection route and the running speed of the inspection robot is used for replacing
The inspection robot is at the firstiThe energy consumption calculation model in each selectable routing is as follows:
and solving an optional routing inspection route corresponding to the minimum energy consumption based on the energy consumption calculation model under the optimization function, namely the optimal routing inspection route.
S6, acquiring a local map at an actual position by using the inspection robot, and converting the local map into a global map for matching based on an optimal value of a pre-constructed coordinate transformation parameter to obtain pose information of the inspection robot during autonomous inspection.
It should be explained that the construction method of the local map at the actual position of the inspection robot is the same as the construction method of the world map, the image of the surrounding environment of the position of the inspection robot is obtained through visual scanning, then the image is converted into a 3D point cloud image based on a pre-constructed Graph-SLAM algorithm, and the local map and the coordinate system are built according to the image.
It is emphasized that the initial coordinate transformation parameters obtained based on the odometer reading have large errors, and thus need to be optimized, which is also a significant problem to be solved by the present invention. The invention can greatly improve the positioning precision of the inspection robot in the inspection process by establishing the optimized value of the coordinate transformation parameter, and obtain accurate position information.
In detail, the converting the local map to the global map based on the optimal value of the pre-constructed coordinate transformation parameter for matching includes:
obtaining an odometer reading;
acquiring initial coordinate transformation parameters based on the odometer reading;
mapping the point cloud in the local map into the global map based on the initial coordinate transformation parameters, and establishing a probability distribution function of the point cloud, wherein the probability distribution function is shown in the following formula:
wherein ,qis a point cloudxThe position average in the voxel unit,
is the variance of the point cloud;
acquiring the sum of probability distribution of all point clouds according to all probability distribution functions;
obtaining a score value of a coordinate transformation parameter based on the sum of the point cloud probability distributions;
optimizing the coordinate transformation parameter score value based on a Hessian matrix method to obtain an optimized value, and selecting the maximum value of the optimized value;
and obtaining the optimal value of the coordinate transformation parameter based on the maximum value of the optimal value.
It is to be understood that an odometer is a method of estimating a change in the position of an object over time using data obtained from a motion sensor. Typical odometer positioning methods include wheel odometers, visual odometers, and visual inertial odometers. According to the invention, the distance and direction angle change quantity of the inspection robot relative to the ground is calculated through the odometer, so that the relative change of the pose of the mobile robot is calculated, and the initial coordinate transformation parameters are established.
In detail, coordinates of the inspection robot mapped to the global map coordinate system according to the coordinate transformation parameters are expressed by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z ]Representing coordinates of the inspection robot i in the local map,t=[t x ，t y ，t z ]indicating inspection machineTranslation of the robot i in the x, y, z-axis directions [r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s= sin/>
，c=cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis;
s7, calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route.
In detail, the calculating the yaw angle based on the pose information and the energy consumption optimal inspection route of the inspection robot includes:
establishing local navigation target points based on optimal routing inspection routeP(p x ，p y ) The distance between the local target point and the robot is fixed, and the whole course is on the optimal inspection route;
the yaw angle is calculated by:
wherein ,
the yaw angle of the inspection robot is represented, (x, y) represents the coordinates of the inspection robot in a world coordinate system, and the yaw angle of the inspection robot is represented by the x, yp x ，p y ) Representing local navigation target points PCoordinates in the world coordinate system.
S8, driving the inspection robot to complete navigation based on pose information and yaw angle of the inspection robot.
In detail, the navigation is accomplished to the robot is patrolled and examined based on the pose information and yaw angle drive of robot, includes:
acquiring PWM signals based on pose information and yaw angle of the inspection robot;
the inspection robot is controlled to perform straight running and steering movement through PWM signals;
when the inspection robot finds an obstacle in the moving process, a pre-built dynamic window method is adopted to reconstruct an inspection route set, and a new optimal inspection route is obtained to finish navigation.
It should be understood that the dynamic window method (Dynamic Window Approach, DWA) is a method for obstacle avoidance planning, and the speed of each period of the robot is controlled based on the DWA algorithm to make a local real-time obstacle avoidance route on the global map.
It is to be explained that the servo driver of the inspection robot can control the motor to rotate through the PWM signal, and the linear running and the left-right differential steering movement of the inspection robot are realized by matching with the wheels, so that the corresponding posture adjustment is performed, the inspection robot returns to a preset optimal inspection route, normal inspection tasks are performed, and navigation is completed.
In order to solve the problems in the background technology, a global map of the surrounding environment is firstly constructed by adopting a pre-constructed visual SLAM technology, then an optional inspection route set of the inspection robot is obtained based on the global map and the target position, an optimization function of the optional inspection route set and the travel speed of the inspection robot is constructed, a relation model of motor voltage and battery voltage of the inspection robot is obtained, an energy consumption calculation model of the inspection robot is constructed based on the relation model, and an energy consumption optimal inspection route from the optional inspection route set to the target position is selected based on the optimization function and the energy consumption calculation model. Therefore, the method for constructing the global map does not need to lay fixed tracks in advance, obtains the inspection route set by the method for constructing the global map, and finally selects the inspection route with optimal energy consumption, so that the method is high in flexibility and low in inspection cost. In addition, the local map at the actual position is obtained by the inspection robot, the local map is converted into the global map for matching based on the optimal value of the pre-constructed coordinate transformation parameter, and the pose information of the inspection robot during autonomous inspection is obtained. Therefore, the positioning of the inspection robot is obtained based on the optimal value of the coordinate transformation parameter, and the coordinate transformation parameter obtained by the odometer is optimized, so that the positioning accuracy is improved. Therefore, the navigation method, the navigation device, the electronic equipment and the computer readable storage medium of the inspection robot can solve the problems that the inspection robot depends on a fixed track, and has poor flexibility, high inspection cost and poor navigation positioning accuracy.
Embodiment two:
fig. 2 is a functional block diagram of a navigation device of a inspection robot according to an embodiment of the present invention.
The navigation device 100 of the inspection robot according to the present invention may be mounted in an electronic apparatus. Depending on the functions implemented, the navigation device 100 of the inspection robot may include an inspection target determination module 101, a global map and optional inspection route construction module 102, an optimal inspection route selection module 103, a pose and yaw calculation module 104, and a navigation module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
The inspection target determining module 101 is configured to receive an instruction for starting the inspection robot, start the inspection robot according to the instruction, and determine a target position of the inspection robot, where the inspection robot hardware platform is composed of a depth camera, a main control unit, and a robot chassis;
the global map and optional inspection route construction module 102 is configured to construct a global map of a surrounding environment by using a pre-constructed visual SLAM technology, and acquire an optional inspection route set of the inspection robot based on the global map and a target position of the inspection robot;
The optimal inspection route selection module 103 is configured to construct an optimization function of an optional inspection route set and a driving speed of the inspection robot, obtain a relationship model of a motor voltage and a battery voltage of the inspection robot, construct an energy loss calculation model of the inspection robot based on the relationship model, and select an energy consumption optimal inspection route from the optional inspection route set to a target position based on the optimization function and the energy loss calculation model;
the pose and yaw angle calculation module 104 is configured to obtain a local map at an actual position by using the inspection robot, convert the local map into a world coordinate system of a global map based on an optimal value of a pre-constructed coordinate transformation parameter for matching, and obtain pose information of the inspection robot during autonomous inspection, where coordinates of the inspection robot mapped to the global map coordinate system according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z]Representing coordinates of the inspection robot i in the local map,t=[t x ，t y ，t z ]representing the translation of inspection robot i in the x, y, z directions [r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown, s= sin/>
，c=cos/>
，/>
And the included angle between the motion direction of the inspection robot i and the y axis is shown.
Calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
the navigation module 105 is configured to drive the inspection robot to complete navigation based on pose information and yaw angle of the inspection robot.
In detail, the modules in the navigation device 100 of the inspection robot in the embodiment of the present invention use the same technical means as the navigation method of the inspection robot described in fig. 1, and can generate the same technical effects, which are not described herein.
Embodiment III:
fig. 3 is a schematic structural diagram of an electronic device for implementing a navigation method of a patrol robot according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a navigation method of a patrol robot.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various types of data, such as codes of navigation methods of the inspection robot, but also for temporarily storing data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects respective parts of the entire electronic device using various interfaces and lines, executes or executes programs or modules (for example, a navigation method of a patrol robot, etc.) stored in the memory 11, and invokes data stored in the memory 11 to perform various functions of the electronic device 1 and process the data.
The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The navigation method of the inspection robot stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, and when running in the processor 10, it can be implemented:
receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein a hardware platform of the inspection robot consists of a depth camera, a main control unit and a robot chassis;
Constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology;
acquiring an optional inspection route set of the inspection robot based on the global map and the target position, and constructing an optimization function of the optional inspection route set and the travelling speed of the inspection robot;
acquiring a relation model of motor voltage and battery voltage of the inspection robot, and constructing an energy loss calculation model of the inspection robot based on the relation model, wherein the energy loss calculation model comprises the length of an optional inspection route set;
based on the optimization function and the energy consumption calculation model, selecting an energy consumption optimal inspection route from the selectable inspection route set to the target position;
the method comprises the steps of obtaining a local map at an actual position by using a patrol robot, converting the local map into a global map based on an optimal value of a pre-constructed coordinate transformation parameter to be matched, and obtaining pose information of the patrol robot during autonomous patrol, wherein coordinates of the patrol robot mapped to a global map coordinate system according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z]Representing coordinates of the inspection robot i in the local map, t=[t x ，t y ，t z ]Representing the translation of inspection robot i in the x, y, z directions [r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s= sin/>
，c=cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis;
calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
and driving the inspection robot to complete navigation based on the pose information and the yaw angle of the inspection robot.
Specifically, the specific implementation method of the above instruction by the processor 10 may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to 2, which are not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein a hardware platform of the inspection robot consists of a depth camera, a main control unit and a robot chassis;
constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology;
acquiring an optional inspection route set of the inspection robot based on the global map and the target position, and constructing an optimization function of the optional inspection route set and the travelling speed of the inspection robot;
acquiring a relation model of motor voltage and battery voltage of the inspection robot, and constructing an energy loss calculation model of the inspection robot based on the relation model, wherein the energy loss calculation model comprises the length of an optional inspection route set;
based on the optimization function and the energy consumption calculation model, selecting an energy consumption optimal inspection route from the selectable inspection route set to the target position;
the method comprises the steps of obtaining a local map at an actual position by using a patrol robot, converting the local map into a global map based on an optimal value of a pre-constructed coordinate transformation parameter to be matched, and obtaining pose information of the patrol robot during autonomous patrol, wherein coordinates of the patrol robot mapped to a global map coordinate system according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z]Representing coordinates of the inspection robot i in the local map,t=[t x ，t y ，t z ]representing the translation of inspection robot i in the x, y, z directions [r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s= sin/>
，c=cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis;
calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
and driving the inspection robot to complete navigation based on the pose information and the yaw angle of the inspection robot.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. A navigation method of a patrol robot, the method comprising:
receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein a hardware platform of the inspection robot consists of a depth camera, a main control unit and a robot chassis;
Constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology;
acquiring an optional inspection route set of the inspection robot based on the global map and the target position, and constructing an optimization function of the optional inspection route set and the travelling speed of the inspection robot;
acquiring a relation model of motor voltage and battery voltage of the inspection robot, and constructing an energy loss calculation model of the inspection robot based on the relation model, wherein the energy loss calculation model comprises the length of an optional inspection route set;
based on the optimization function and the energy consumption calculation model, selecting an energy consumption optimal inspection route from the selectable inspection route set to the target position;
the method comprises the steps of obtaining a local map at an actual position by using a patrol robot, converting the local map into a global map based on an optimal value of a pre-constructed coordinate transformation parameter to be matched, and obtaining pose information of the patrol robot during autonomous patrol, wherein coordinates of the patrol robot mapped to the global map according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z ]Representing coordinates of the inspection robot i in the local map, t =[ t x ，t y ，t z ]Representation ofTranslation amount of inspection robot i in x, y and z axis directions [ r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s = sin/>
，c =cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis;
calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
and driving the inspection robot to complete navigation based on the pose information and the yaw angle of the inspection robot.
2. The method for navigating a patrol robot according to claim 1, wherein the depth camera used by the patrol robot is an ASTRA depth camera, which is mounted on top of the robot;
the robot chassis consists of a control chip, a battery, a servo driver, a motor and wheels.
3. The navigation method of the inspection robot according to claim 1, wherein the constructing a global map of the surrounding environment using the pre-constructed visual SLAM technique includes:
receiving a depth camera image;
based on a pre-constructed Graph-SLAM algorithm, outputting a 3D point cloud image according to a depth camera image, and establishing a world coordinate system in the 3D point cloud image;
And integrating the 3D point cloud image in the world coordinate system based on a pre-constructed coordinate conversion method to obtain a global map.
4. The method for navigating a patrol robot according to claim 1, wherein said constructing an optimization function of the set of selectable patrol routes and the travel speed of the patrol robot comprises:
performing segmentation on the selectable routing set based on the target position to obtain a plurality of groups of segmented routing sets;
receiving an optimized adjustment factor of the inspection route and the inspection robot;
acquiring the number of inspection robots running on an inspection route;
calculating the crowdedness of the inspection route based on the number of the inspection robots;
calculating an optimization function of the running speed of each segment inspection route and the inspection robot in each group of segment inspection route set based on the optimization adjustment factors and the crowdedness degree:
wherein ,
indicating that the inspection robot is driving at +.>
The +.f. of the alternative route>
The speed of travel of the individual section of the route, +.>
Indicating the initial running speed of the inspection robot, < + >>
Indicate->
Each sectional inspection routeOptimal regulation factor with inspection robot, < ->
Indicating the +.f in the selectable tour route set>
The +.f. of the alternative route>
Congestion degree of each segment inspection route.
5. The method for navigating the inspection robot according to claim 1, wherein the obtaining a relation model of the motor voltage and the battery voltage of the inspection robot comprises:
receiving the duty ratio of a patrol robot battery by adopting a PWM technology, the internal resistance of a motor, the counter electromotive force coefficient of the motor, the reduction ratio of a motor speed reducer, the rotating speed of the motor and the working current of the motor;
based on the duty ratio of the battery adopting the PWM technology, the internal resistance of the motor, the counter electromotive force coefficient of the motor, the reduction ratio of a motor speed reducer, the motor rotating speed and the motor working current, a relation model of the motor voltage and the battery voltage of the inspection robot is constructed as shown in the following formula:
wherein ,
represents the motor voltage>
Represents battery voltage, < >>
Indicating the duty cycle of the battery using PWM technique, +.>
Representing the motor current of the motor when in operation, +.>
Is the internal resistance of the motor>
For the back emf coefficient of the motor>
Is the speed reduction ratio of the motor speed reducer, +.>
Indicated at motor current +.>
The motor speed in the case is determined.
6. The method for navigating a patrol robot according to claim 5, wherein said constructing a patrol robot energy loss calculation model based on said relation model comprises:
Acquiring the inspection robot at the first positioniSelectable tour routejRoute length of each sectional inspection route;
according to the route length, constructing an energy loss calculation model of the inspection robot as shown in the following formula:
wherein ,
represents the energy consumption value of the inspection robot, < ->
Indicate->
The selectable tour route +.>
Route length of each segment inspection route.
7. A navigation method of a patrol robot according to claim 3, wherein said converting the local map into a global map based on the optimal value of the pre-constructed coordinate transformation parameter for matching comprises:
obtaining an odometer reading;
acquiring initial coordinate transformation parameters based on the odometer reading;
mapping the point cloud in the local map into the global map based on the initial coordinate transformation parameters, and establishing a probability distribution function of the point cloud, wherein the probability distribution function is shown in the following formula:
wherein ,qis a point cloudxThe position average in the voxel unit,
is the variance of the point cloud;
acquiring the sum of probability distribution of all point clouds according to the probability distribution function;
obtaining a score value of the coordinate transformation parameter based on the sum of all the point cloud probability distributions;
optimizing the fractional value of the coordinate transformation parameter based on a pre-constructed Hessian matrix method to obtain an optimized value, and selecting the maximum value of the optimized value;
And obtaining the optimal value of the coordinate transformation parameter based on the maximum value of the optimal value.
8. The navigation method of the inspection robot according to claim 1, wherein the calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route includes:
establishing local navigation target points based on optimal routing inspection routeP ( p x ，p y ) The distance between the local target point and the robot is fixed, and the whole course is on the optimal inspection route;
the yaw angle is calculated by:
wherein ,
the yaw angle of the inspection robot is represented, (x, y) represents the coordinates of the inspection robot in a world coordinate system, and the yaw angle of the inspection robot is represented by the x, y p x ， p y ) Representing local navigation target pointsPCoordinates in the world coordinate system.
9. The method for navigating the inspection robot according to claim 8, wherein the driving the inspection robot to navigate based on pose information and yaw angle of the inspection robot comprises:
acquiring PWM signals based on pose information and yaw angle of the inspection robot;
the inspection robot is controlled to perform straight running and steering movement through PWM signals;
when the inspection robot finds an obstacle in the moving process, a pre-constructed dynamic window method is adopted to reconstruct an optional inspection route set, and a new optimal inspection route is obtained to finish navigation.
10. A navigation device for a patrol robot, the device comprising:
the inspection target determining module is used for receiving a starting instruction of the inspection robot, starting the inspection robot according to the starting instruction, and determining a target position of the inspection robot, wherein the inspection robot hardware platform consists of a depth camera, a main control unit and a robot chassis;
the global map and optional routing inspection route construction module is used for constructing a global map of the surrounding environment by adopting a pre-constructed visual SLAM technology and acquiring an optional routing inspection route set of the inspection robot based on the global map and the target position;
the optimal inspection route selection module is used for constructing an optimization function of an optional inspection route set and the running speed of the inspection robot, obtaining a relation model of the motor voltage and the battery voltage of the inspection robot, constructing an energy loss calculation model of the inspection robot based on the relation model, and selecting an energy consumption optimal inspection route from the optional inspection route set to a target position based on the optimization function and the energy loss calculation model;
the position and yaw angle calculation module is used for acquiring a local map at an actual position by using the inspection robot, converting the local map into a global map for matching based on an optimal value of a pre-constructed coordinate transformation parameter to obtain position information of the inspection robot during autonomous inspection, wherein coordinates of the inspection robot mapped to a global map coordinate system according to the coordinate transformation parameter are represented by the following formula:
in the formula ,
representing coordinates of inspection robot i in global map,/->
=[x，y，z ]Representing coordinates of the inspection robot i in the local map,t =[ t x ，t y ，t z ]representing the translation of inspection robot i in the x, y, z directions [ r x ，r y ， r z ]The rotation amount of the inspection robot i in the x, y and z axis directions is shown,s = sin/>
，c =cos/>
，/>
representing an included angle between the motion direction of the inspection robot i and the y axis; calculating a yaw angle based on pose information of the inspection robot and an energy consumption optimal inspection route, wherein the yaw angle is an included angle between the movement direction of the inspection robot and the energy consumption optimal inspection route;
and the navigation module is used for driving the inspection robot to finish navigation based on the pose information and the yaw angle of the inspection robot.
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