Robot intelligent control method and system driven by multi-dimensional geographic information

Abstract

The present invention belongs to the field of robot technology, and discloses a robot intelligent control method and system driven by multi-dimensional geographic information, the method comprising: obtaining the first position of the robot, obtaining the first coordinate of the center position of the first functional component of the robot head based on the first position, collecting the second coordinate at the center point of the target object, obtaining the straight line connecting the first coordinate and the second coordinate, controlling the rotation of the robot head based on the straight line connecting the first coordinate, making the center position of the first functional component focus and lock the target object, determining the key point for observing the target object based on the second coordinate, and obtaining the second position of the key point, planning the robot's travel direction and driving route based on the first position and the second position, and controlling the robot to move to the key point. The technical solution of the present invention can lock the target in real time and observe the target at the key position, which effectively improves the work efficiency and intelligence level of the robot.

Description

Technical Field

[0001] The present invention belongs to the field of robot technology, and in particular relates to a robot intelligent control method and system driven by multi-dimensional geographic information. Background Art

[0002] With the development of artificial intelligence technology, artificial intelligence robots are increasingly being used in all walks of life. Whether it is replacing human operations or joining industrial production to improve the intelligence of production lines, they play an important role and become products urgently needed by many industries. Among them, using robots to observe and reconnaissance target objects is also an important direction of robot research.

[0003] In the prior art, for example, Chinese patent CN115437299A discloses a method and system for controlling the movement of a companion transport robot, which obtains the position information of a UWB beacon and a vehicle-mounted UWB base station in real time; obtains multiple sets of data correspondingly collected by multiple vehicle-mounted acquisition devices in real time, and the multiple vehicle-mounted acquisition devices face different directions around the vehicle body, and each set of data includes image data and distance data; when the position information is received, the first motion parameter of the robot is calculated according to the position information, and the movement of the robot is controlled according to the first motion parameter; when the position information is not received, the following target position is calculated according to the multiple sets of data, the second motion parameter of the robot is calculated according to the following target position, and the movement of the robot is controlled according to the second motion parameter. Another example is Chinese patent CN108885436A, which discloses an autonomous surveillance robot system, including a chassis; a drive that supports the chassis above a floor surface in a home and is configured to move the chassis across the floor surface; a variable height member that is connected to the chassis and can extend vertically; a camera supported by the variable height member; and a controller that is configured to operate the drive to navigate the robot to a location within the home, adjust the height of the variable height member when reaching a first location, and operate the camera to capture a digital image of the home at the first location when the variable height member is at the adjusted height.

[0004] In the above two existing technologies, the robot does not lock the target, and it is not easy to observe the specific activities of the target during the operation of the robot. Therefore, it is an urgent problem to provide a robot intelligent control method and system driven by multi-dimensional geographic information to improve the working efficiency and intelligence level of the robot. Summary of the invention

[0005] In response to the above-mentioned technical problems, the present invention provides a robot intelligent control method and system driven by multi-dimensional geographic information.

[0006] In a first aspect, the present invention provides a robot intelligent control method driven by multi-dimensional geographic information, the method comprising the following steps:

[0007] Step 1: Obtain a first position of the robot, and obtain a first coordinate of a center position of a first functional component of the robot head based on the first position, wherein the first position is a three-dimensional coordinate of a positioning module of the robot;

[0008] Step 2: Collect the second coordinates at the center point of the target object, obtain the straight line connecting the first coordinates and the second coordinates, and control the rotation of the robot head based on the straight line connecting the first functional component so that the center position of the first functional component is focused and locked on the target object;

[0009] Step 3: determining a key point for observing the target object based on the second coordinate, and obtaining a second position of the key point;

[0010] Step 4: Plan the robot's travel direction and route based on the first position and the second position, and control the robot to move to the key point.

[0011] Specifically, the target object is a person, a vehicle, or an object.

[0012] Specifically, in step 2, controlling the robot head to rotate based on the straight connecting line includes:

[0013] Acquire in real time a first straight line at the center of the first functional component where the front side faces, and calculate a horizontal angle between the first straight line and a straight line connecting line, and a vertical angle between the first straight line and a straight line connecting line;

[0014] The robot head is controlled to rotate based on the horizontal angle and the vertical angle.

[0015] Specifically, in step 4, when controlling the robot to move to the key point, if a first obstacle is detected in the target area in the robot's driving direction, the following operations are performed:

[0016] Step 41, obtaining the third position and the first speed of the robot at the current moment, and obtaining the fourth position and the second speed of the first obstacle, wherein the current moment is the moment when the first obstacle is detected;

[0017] Step 42: judging whether the robot will collide with the first obstacle based on the third position, the first speed, the fourth position and the second speed; if not, continuing to travel along the travel route at the first speed; if yes, proceeding to step 43;

[0018] Step 43, calculating a first encounter time when the distance between the bottom center point of the robot and the bottom center point of the first obstacle is a first preset distance and a first encounter position of the first obstacle;

[0019] Step 44: Generate a first-category driving route and a second-category driving route based on the first encounter time and the first encounter position, respectively, wherein the first-category driving route is a newly planned route traveling at a first speed, and the second-category driving route is a newly planned route traveling at a speed different from the first speed;

[0020] Step 45: Obtain a new driving route from the first type of driving route and the second type of driving route according to a preset rule, and control the robot to drive according to the new driving route.

[0021] Specifically, in step 44, generating the first type of driving route includes the following steps:

[0022] Step 4411, extracting a connecting line between the third position and the second position, and defining a straight line passing through the first meeting position and perpendicular to the connecting line as a first reference line;

[0023] Step 4412: setting two adjustment nodes on the first reference line at a first preset distance from the first encounter position, defining the adjustment node close to the first obstacle as the first adjustment node, and defining the adjustment node far from the first obstacle as the second adjustment node;

[0024] Step 4413: define a straight line passing through the reference node and parallel to the connecting line as a second reference line, set a point on the second reference line close to the robot and at a second preset distance from the reference node as a third adjustment node, and set a point on the second reference line close to the key point and at a third preset distance from the reference node as a fourth adjustment node, wherein the reference node is the first adjustment node or the second adjustment node;

[0025] Step 4414: set a point on the driving route that is at a fourth preset distance from the fourth adjustment node as the fifth adjustment node, and then generate a first-type reference driving route based on the third position, the position of the third adjustment node, the position of the reference node, the position of the fourth adjustment node, the position of the fifth adjustment node, and the driving route;

[0026] Step 4415: When the reference node is the second adjustment node, proceed to step 4416; when the reference node is the first adjustment node, proceed to step 4418;

[0027] Step 4416: Calculate the adjustment time for the robot to reach the reference node, and calculate the time difference between the adjustment time and the first encounter time, and determine whether the time difference is within a preset range. If so, define the first-class reference driving route as the first-class driving route. If not, proceed to step 4417.

[0028] Step 4417: based on the first type of reference driving route, repeat step 43 to calculate a new first meeting time and a new first meeting position, then repeat step 4411, and then set a new second adjustment node on the first reference line on the side of the connecting line away from the first obstacle, and then repeat steps 4413 to 4417;

[0029] Step 4418: Based on the first type of reference driving route, determine whether the robot will collide with the first obstacle. If not, proceed to step 4419; if yes, proceed to step 4420.

[0030] Step 4419: Set a new first adjustment node on the first reference line at a position that is located on the side of the first adjustment node away from the first obstacle and at a position that is a fifth preset distance from the first adjustment node, and repeat steps 4413 to 4414. Then, based on the first-class reference driving route, determine whether the robot and the first obstacle will collide. If not, repeat step 4419. If yes, define the first-class reference driving route when it was determined last time that there would be no collision as the first-class driving route.

[0031] Step 4420: Based on the first type of reference driving route, repeat step 43 to calculate a new first encounter time and a new first encounter position, then repeat step 4411, and then set a new first adjustment node on the first reference line on the side of the connecting line close to the first obstacle, and then repeat steps 4413 to 4415, and steps 4413 to 4420.

[0032] Specifically, in step 44, generating the second type of driving route includes the following steps:

[0033] Step 4421, extracting a connecting line between the third position and the second position, and defining a straight line passing through the first meeting position and perpendicular to the connecting line as a first reference line;

[0034] Step 4422: Generate a third reference line with the fourth position as an endpoint and the travel direction of the first obstacle as an extension direction, then set N1 second meeting positions on the third reference line close to the first obstacle and set N2 second meeting positions on the first reference line away from the first obstacle at intervals of a sixth preset distance with the first meeting position as a reference point;

[0035] Step 4423: Generate two second-category reference driving routes for the first meeting position and any second meeting position according to the method of step 4412 to step 4414, then delete duplicate routes to obtain the second-category driving route;

[0036] Step 4424: For any second-type driving route, control the robot to change speed between the third position and the third adjustment node, and after passing the third adjustment node, drive at a constant speed according to the first speed, so that the time when the robot reaches the reference node is the same as the time when the first obstacle reaches the encounter position, wherein the encounter position is the first encounter position or the second encounter position.

[0037] Specifically, in step 45, the driving routes that the robot cannot pass through in the first and second driving routes are deleted to obtain a set of pending driving routes, and then the moving cost of each pending driving route is calculated, and the pending driving route with the smallest moving cost is used as the new driving route. The calculation formula of the moving cost is:

[0038] ,

[0039] Among them, C i is the travel cost of the i-th undetermined travel route, α1 and α2 are parameter weight coefficients, S i is the total length of the i-th pending driving route, T i is the time to reach the second location via the i-th pending driving route.

[0040] Specifically, the method for obtaining the robot position includes:

[0041] Step 11: Obtain the estimated position of the robot and the first three-dimensional coordinate point set collected by the data acquisition device;

[0042] Step 12: Based on the estimated position and the collection range of the data collection device, calculate the collection area corresponding to the first three-dimensional coordinate point set, and obtain the second three-dimensional coordinate point set from the first storage module based on the collection area, wherein the first storage module stores a standard three-dimensional coordinate point set of the area where the robot is located;

[0043] Step 13, determining whether the second storage module stores an unrecognizable area, if yes, deleting the three-dimensional coordinate point corresponding to the unrecognizable area from the second three-dimensional coordinate point set, generating a new second three-dimensional coordinate point set, and then proceeding to step 14, if no, directly proceeding to step 14;

[0044] Step 14, calculating the total number of three-dimensional coordinate points in the second three-dimensional coordinate point set, and determining whether the total number is equal to the standard value. If so, directly proceeding to step 15; if not, adding or deleting the second three-dimensional coordinate point set to generate a third three-dimensional coordinate point set, wherein the number of three-dimensional coordinate points in the third three-dimensional coordinate point set is equal to the standard value;

[0045] Step 15: Match the first three-dimensional coordinate point set and the reference three-dimensional coordinate point set, and then adjust the estimated position based on the matching result to obtain the robot position, wherein the reference three-dimensional coordinate point set is the second three-dimensional coordinate point set or the third three-dimensional coordinate point set.

[0046] Specifically, after step 15, the method further includes:

[0047] Step 16, determining whether there is a second obstacle in the acquisition area, if not, deleting the unrecognizable area in the second storage module, if yes, proceeding to step 17;

[0048] Step 17: obtaining the contour and the fifth position of the second obstacle, and extracting the blocked portion of the second three-dimensional coordinate point set blocked by the second obstacle based on the contour and the fifth position;

[0049] Step 18: Obtain the three-dimensional outline corresponding to the blocked part, and define the area surrounded by the three-dimensional outline as an unrecognizable area.

[0050] In a second aspect, the present invention further provides a robot intelligent control system driven by multi-dimensional geographic information, the system comprising: a computing control unit, a positioning module and a data receiving module, the computing control unit comprising a first computing module, a direction control module, a route planning module and a walking control module;

[0051] A positioning module, used to obtain a first position of the robot, wherein the first position is a three-dimensional coordinate of the robot positioning module;

[0052] A first calculation module, used for obtaining a first coordinate of a center position of a first functional component of the robot head according to the first position;

[0053] A data receiving module, used for collecting the second coordinate of the center point of the target object;

[0054] The orientation control module is further used to obtain a straight line connecting the first coordinate and the second coordinate, and control the rotation of the robot head based on the straight line connecting the first coordinate so that the center position of the first functional component is focused and locked on the target object;

[0055] The first calculation module is further used to determine a key point for observing the target object according to the second coordinates, and obtain a second position of the key point;

[0056] A route planning module, used to plan the travel direction and travel route of the robot according to the first position and the second position;

[0057] Walking control module, used to control the robot to move to key points.

[0058] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0059] In the present invention, firstly, the first coordinate of the center position of the first functional component of the robot head is calculated based on the position of the robot, then the second coordinate at the center point of the target object is collected, the straight line connecting the first coordinate and the second coordinate is obtained, and the robot head is controlled to rotate based on the straight line connecting the first coordinate so that the center position of the first functional component focuses and locks the target object. Secondly, based on the position of the robot and the position of the target object, the key point position for observing the target is determined. Finally, the robot's travel direction and driving route are planned, the robot is controlled to move to the key point position, and the target object is monitored at the key point position. Through the present invention, the target can be locked in real time, and the visual tracking of the target can be achieved during the movement of the robot. At the same time, the target object is observed at a key position, and the target object is fully observed without affecting the target object, thereby improving the work efficiency and intelligence level of the robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0061] Figure 1 A flowchart of the multi-dimensional geographic information driven robot intelligent control method of the present invention;

[0062] Figure 2 is a phase relationship diagram when the robot according to an embodiment of the present invention encounters a first obstacle;

[0063] Figure 3 A schematic diagram of generating a first type of driving route according to an embodiment of the present invention;

[0064] Figure 4 A schematic diagram of generating a second type of driving route according to an embodiment of the present invention;

[0065] Figure 5 This is a modular schematic diagram of the multi-dimensional geographic information driven robot intelligent control system of the present invention. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the specific embodiments described herein are only used to explain the present invention and are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0067] It should be noted that if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0068] Figure 1 FIG. 1 is a flow chart of an embodiment of a multi-dimensional geographic information driven robot intelligent control method provided by the present invention, and the flow chart specifically includes the following steps:

[0069] Step 1: Obtain a first position of the robot, and based on the first position, obtain a first coordinate of a center position of a first functional component of the robot head, wherein the first position is a three-dimensional coordinate of a positioning module of the robot.

[0070] Exemplarily, the first functional component is a visual screen, an image acquisition component, a visual component, etc. on the robot head.

[0071] Step 2: Collect the second coordinate at the center point of the target object, obtain the straight line connecting the first coordinate and the second coordinate, and control the rotation of the robot head based on the straight line to focus and lock the target object at the center position of the first functional component.

[0072] Specifically, the target object is a person, a vehicle, or an object.

[0073] Specifically, in step 2, controlling the robot head to rotate based on the straight connecting line includes:

[0074] Acquire in real time a first straight line at the center of the first functional component where the front side faces, and calculate a horizontal angle between the first straight line and a straight line connecting line, and a vertical angle between the first straight line and a straight line connecting line;

[0075] The robot head is controlled to rotate based on the horizontal angle and the vertical angle.

[0076] Preferably, during the movement of the robot, steps 1 to 2 are repeated so that the robot can always lock onto the target and observe the target object in real time.

[0077] Step 3: Determine the key point for observing the target object based on the second coordinate, and obtain the second position of the key point.

[0078] The above key points are the best positions for observing the target object. The selection of key points can be achieved through existing technologies and will not be described in detail here.

[0079] Step 4: Plan the robot's travel direction and route based on the first position and the second position, and control the robot to move to the key point.

[0080] The above positions or coordinates are all latitude, longitude and altitude information, or X, Y, and Z coordinates in the geodetic coordinate system.

[0081] On the basis of the above, the robot can be triggered to lock and control the target. The target can include people, cars, objects, etc. Anything visible can be used as a target. On the basis of the above, the robot and peripheral equipment can be interconnected and share information with the robot as the center, and complete complex tasks of great strategic significance through clustered deployment.

[0082] Specifically, in step 4, when controlling the robot to move to the key point, if a first obstacle is detected in the target area in the robot's driving direction, the following operations are performed:

[0083] Step 41, obtaining the third position and first speed of the robot at the current moment, and obtaining the fourth position and second speed of the first obstacle, wherein the current moment is the moment when the first obstacle is detected.

[0084] Step 42: determine whether the robot will collide with the first obstacle based on the third position, the first speed, the fourth position and the second speed; if not, continue to travel along the driving route at the first speed; if yes, proceed to step 43.

[0085] Step 43: Calculate a first encounter time when the distance between the bottom center point of the robot and the bottom center point of the first obstacle is a first preset distance and a first encounter position of the first obstacle.

[0086] Step 44: Generate a first type of driving route and a second type of driving route based on the first meeting time and the first meeting position, respectively, wherein the first type of driving route is a newly planned route traveling at a first speed, and the second type of driving route is a newly planned route traveling at a speed different from the first speed.

[0087] Step 45: Obtain a new driving route from the first type of driving route and the second type of driving route according to a preset rule, and control the robot to drive according to the new driving route.

[0088] The target area may be a detection area in the driving direction of the robot, and the range of the detection area is preset by the system or generated by obtaining instructions input by the user.

[0089] Sensors are installed on the robot to obtain the robot's own position information and speed information, as well as the position information and speed information of obstacles. The position information and speed information of obstacles can also be obtained through sensors installed at certain fixed positions in the environment.

[0090] The first preset distance is set according to the experience of those skilled in the art or according to the actual application scenario, and the embodiment of the present application does not limit this. Preferably, the first preset distance is obtained according to the diameter of the robot and the first obstacle, and the calculation formula of the first preset distance is:

[0091]

[0092] Among them, DP1 is the first preset distance, β is the parameter weight coefficient, D R is the maximum diameter of the robot, D O is the maximum diameter of the first obstacle.

[0093] When the center point of the bottom of the robot is at a first preset distance from the center point of the bottom of the first obstacle, the robot and the first obstacle begin to contact, and then the interface becomes larger and they will collide. Figure 2 As shown, A is the first encounter position of the first obstacle.

[0094] Specifically, in step 44, generating the first type of driving route includes the following steps:

[0095] Step 4411: extract a connecting line between the third position and the second position, and define a straight line passing through the first meeting position and perpendicular to the connecting line as a first reference line.

[0096] Step 4412: two adjustment nodes are respectively set on the first reference line at a first preset distance from the first meeting position, and the adjustment node close to the first obstacle is defined as the first adjustment node, and the adjustment node far from the first obstacle is defined as the second adjustment node.

[0097] Step 4413, define the straight line passing through the reference node and parallel to the connecting line as the second reference line, set the point on the second reference line, close to the robot side, and at a second preset distance from the reference node as the third adjustment node, and set the point on the second reference line, close to the key point side, and at a third preset distance from the reference node as the fourth adjustment node, wherein the reference node is the first adjustment node or the second adjustment node.

[0098] Step 4414: set the point on the driving route that is at a fourth preset distance vertically from the fourth adjustment node as the fifth adjustment node, and then generate a first type of reference driving route based on the third position, the position of the third adjustment node, the position of the reference node, the position of the fourth adjustment node, the position of the fifth adjustment node and the driving route.

[0099] Step 4415: When the reference node is the second adjustment node, proceed to step 4416; when the reference node is the first adjustment node, proceed to step 4418.

[0100] Step 4416, calculate the adjustment time for the robot to reach the reference node, and calculate the time difference between the adjustment time and the first encounter time, and determine whether the time difference is within a preset range. If so, define the first-class reference driving route as the first-class driving route. If not, enter step 4417.

[0101] Step 4417: Based on the first type of reference driving route, repeat step 43 to calculate a new first encounter time and a new first encounter position, then repeat step 4411, and then set a new second adjustment node on the first reference line on the side of the connecting line away from the first obstacle, and then repeat steps 4413 to 4417.

[0102] Step 4418: Based on the first type of reference driving route, determine whether the robot and the first obstacle will collide. If not, proceed to step 4419; if yes, proceed to step 4420.

[0103] Step 4419: Set a new first adjustment node on the first reference line, on the side of the first adjustment node away from the first obstacle and at a position the fifth preset distance from the first adjustment node, and repeat steps 4413 to 4414. Then, based on the first type of reference driving route, determine whether the robot and the first obstacle will collide. If not, repeat step 4419. If so, define the first type of reference driving route when it was last determined that there would be no collision as the first type of driving route.

[0104] Step 4420: Based on the first type of reference driving route, repeat step 43 to calculate a new first encounter time and a new first encounter position, then repeat step 4411, and then set a new first adjustment node on the first reference line on the side of the connecting line close to the first obstacle, and then repeat steps 4413 to 4415, and steps 4413 to 4420.

[0105] The second preset distance, the third preset distance, the fourth preset distance and the fifth preset distance are set according to the experience of those skilled in the art or according to the actual application scenario, and the embodiment of the present application does not limit this. For example, the second preset distance is 0.6D R , the third preset distance is 0.7D R The second preset distance and the third preset distance may be different or the same. For example, the fifth preset distance is 0.1 m.

[0106] As a preferred technical solution of the present invention, when the second position is located in front of the third position, step 4411 extracts the connecting line between the third position and the second position; when the second position is not located in front of the third position, the connecting line extracted in step 4411 is the connecting line between the third position and the turning point, and the turning point is a turning point on the driving route that is located in front of the third position.

[0107] At the first adjustment node or the second adjustment node, the distance between the robot and the first obstacle is the smallest. After crossing the first adjustment node or the second adjustment node, the robot and the first obstacle move in different directions, and the distance between their center points will become larger and larger, so there is no possibility of collision. Therefore, the first adjustment node or the second adjustment node is set as the reference point for adjustment.

[0108] by Figure 3 The embodiment of the present invention is described by taking the example as an example. Figure 3 As shown, L is a connecting line, L1 is a first reference line, B1 is a first adjustment node, B2 is a second adjustment node, L2 and L3 are second reference lines, C3 and C4 are respectively a third adjustment node and a fourth adjustment node located on the second reference line L2, D3 and D4 are respectively a third adjustment node and a fourth adjustment node located on the second reference line L3, and E is a fifth adjustment node.

[0109] For generating a driving route with the second adjustment node B2 as the reference point, since the robot travels to the second adjustment node B2 at the first speed, the time used to reach the second adjustment node B2 will be greater than the first encounter time, and the robot and the first obstacle may still collide. Therefore, it is necessary to continue to move the second adjustment node B2 to the left so that the time used by the robot and the first obstacle to reach the set position is the same, to ensure that the robot and the first obstacle will not collide.

[0110] For generating a driving route with the first adjustment node B1 as the reference point, since the robot travels to the first adjustment node B1 at the first speed, the time used to reach the first adjustment node B1 will be greater than the first encounter time. At this time, the first obstacle may have already passed the first encounter position. At this time, there may be a problem that the first adjustment node B1 is to the right, resulting in a problem that the driving route is too long. Therefore, in the case that the robot and the first obstacle will not collide, the first adjustment node B1 is moved to the left so that the time used by the robot and the first obstacle to reach the set position is the same, so as to ensure that the robot and the first obstacle will not collide and ensure that the robot travels the minimum distance. In addition, in the case that the robot and the first obstacle will collide, the first adjustment node B1 is moved to the right according to the method described in step 4420. Preferably, for generating a driving route with the first adjustment node B1 as the reference point, in the case that the robot and the first obstacle will collide, a new first adjustment node can be set on the first reference line L1, located on the right side of the first adjustment node B1 and at a position of the fifth preset distance from the first adjustment node B1, to further generate a new driving route.

[0111] Specifically, in step 44, generating the second type of driving route includes the following steps:

[0112] Step 4421: extract a connecting line between the third position and the second position, and define a straight line passing through the first meeting position and perpendicular to the connecting line as a first reference line.

[0113] Step 4422: Generate a third reference line with the fourth position as the endpoint and the travel direction of the first obstacle as the extension direction. Then, with the first meeting position as the reference point, set N1 second meeting positions on the third reference line close to the first obstacle and set N2 second meeting positions on the first reference line away from the first obstacle at intervals of a sixth preset distance.

[0114] Step 4423: According to the method of steps 4412 to 4414, two second-category reference driving routes are generated for the first meeting position and any second meeting position, and then duplicate routes are deleted to obtain the second-category driving route.

[0115] Step 4424: For any second-type driving route, control the robot to change speed between the third position and the third adjustment node, and after passing the third adjustment node, drive at a constant speed according to the first speed, so that the time when the robot reaches the reference node is the same as the time when the first obstacle reaches the encounter position, wherein the encounter position is the first encounter position or the second encounter position.

[0116] Preferably, the second meeting position is arranged on the first reference line within a seventh preset distance from the first meeting position.

[0117] The sixth preset distance and the seventh preset distance are set according to the experience of those skilled in the art or according to actual application scenarios, and are not limited in the present embodiment. For example, the sixth preset distance is D R , 0.1m, 0.5m, etc.

[0118] like Figure 4 As shown, L4 is the third reference line. Two second meeting positions (b1 and b2) are set on the side of L4 close to the first obstacle, and two second meeting positions (a1 and a2) are set on the side of L1 away from the first obstacle, and the second type of reference driving route is generated based on each meeting position (the first meeting position and the second meeting position).

[0119] After the robot passes the third adjustment node, it travels at a constant speed according to the first speed, so as to prevent the robot from traveling too fast and causing discomfort to the first obstacle, and to avoid the robot from traveling too slowly and increasing the travel time. Since the travel distance and travel speed of the robot from the first turning point (such as the third adjustment node) to the reference node (such as the first adjustment node) are constant, and the time for the robot to reach the reference node from the third position is also constant, the travel time for the robot to reach the first turning point can be obtained, and the robot is controlled to travel at a variable speed based on the travel time and the distance from the third position to the first turning point, so that the time for the robot to reach the reference node is equal to the time for the first obstacle to reach the encounter position.

[0120] Specifically, in step 45, the driving routes that the robot cannot pass through in the first and second driving routes are deleted to obtain a set of pending driving routes, and then the moving cost of each pending driving route is calculated, and the pending driving route with the smallest moving cost is used as the new driving route. The calculation formula of the moving cost is:

[0121] ,

[0122] Among them, C i is the travel cost of the i-th undetermined travel route, α1 and α2 are parameter weight coefficients, S i is the total length of the i-th pending driving route, T i is the time to reach the second location via the i-th pending driving route.

[0123] Preferably, when obtaining the set of pending driving routes, driving routes whose speed or acceleration exceeds a preset range are deleted from the first category of driving routes and the second category of driving routes.

[0124] According to the technical solution of the present invention, when the robot encounters an obstacle during driving, a new driving route can be quickly generated, thereby improving the efficiency of generating the obstacle avoidance route, allowing the robot to cross the obstacle in the fastest time and shortest distance, thereby improving the obstacle avoidance efficiency.

[0125] Specifically, the method for obtaining the robot position includes:

[0126] Step 11: Obtain the estimated position of the robot and the first three-dimensional coordinate point set collected by the data acquisition device.

[0127] Step 12: Based on the estimated position and the collection range of the data acquisition device, calculate the collection area corresponding to the first three-dimensional coordinate point set, and obtain the second three-dimensional coordinate point set from the first storage module based on the collection area, wherein the first storage module stores the standard three-dimensional coordinate point set of the area where the robot is located.

[0128] Step 13, determine whether the second storage module stores an unrecognizable area. If so, delete the three-dimensional coordinate points corresponding to the unrecognizable area from the second three-dimensional coordinate point set, generate a new second three-dimensional coordinate point set, and then enter step 14. If not, directly enter step 14.

[0129] Step 14, calculate the total number of three-dimensional coordinate points in the second three-dimensional coordinate point set, and determine whether the total number is equal to the standard value. If it is equal, directly proceed to step 15; if it is not equal, add or delete the second three-dimensional coordinate point set to generate a third three-dimensional coordinate point set, wherein the number of three-dimensional coordinate points in the third three-dimensional coordinate point set is equal to the standard value.

[0130] Step 15: Match the first three-dimensional coordinate point set and the reference three-dimensional coordinate point set, and then adjust the estimated position based on the matching result to obtain the robot position, wherein the reference three-dimensional coordinate point set is the second three-dimensional coordinate point set or the third three-dimensional coordinate point set.

[0131] Exemplarily, the estimated position of the robot is a position obtained based on beacon positioning, GPS, etc.

[0132] Exemplarily, the three-dimensional coordinate point set is a set of three-dimensional coordinate points of an object within a scanning range acquired by a three-dimensional laser scanner or a photographic scanner.

[0133] Exemplarily, the standard three-dimensional coordinate point set is the three-dimensional coordinate point set of all fixed objects in the area. When there are moving obstacles in the area, the fixed objects in the area will be blocked, so that the data acquisition device cannot collect the three-dimensional coordinate points of the blocked objects when collecting the three-dimensional coordinate point set, resulting in an unrecognizable area. Therefore, before matching the three-dimensional coordinate point set, the three-dimensional coordinate points corresponding to the unrecognizable area are first deleted from the second three-dimensional coordinate point set to reduce the subsequent calculation processing time.

[0134] Preferably, the standard value is calculated in advance according to the processing capacity of the three-dimensional coordinate point matching module. Exemplarily, the three-dimensional coordinate point matching module is used to perform matching training on a large number of three-dimensional coordinate point sets with different numbers, generate a three-dimensional coordinate point number-processing time relationship function, and then obtain the standard value based on the maximum delay time and the above relationship function. Preferably, the above maximum delay time is set by those skilled in the art to ensure real-time positioning accuracy.

[0135] When the data acquisition device collects the first three-dimensional coordinate point set, for any object within the collection range, the three-dimensional coordinate points of the object far away from the robot cannot be collected or the collection accuracy is low, or, for all objects within the collection range, the farther away from the robot, the lower the collection accuracy. Therefore, when the total number of three-dimensional coordinate points in the second three-dimensional coordinate point set is greater than the standard value, the three-dimensional coordinate points on the side of the object away from the robot are deleted first. If the total number of remaining three-dimensional coordinate points is still greater than the standard value, the three-dimensional coordinate points farther away from the robot are deleted. When the total number of three-dimensional coordinate points in the second three-dimensional coordinate point set is less than the standard value, the three-dimensional coordinate points of the object close to the robot are added first.

[0136] According to the technical solution of the present invention, when performing three-dimensional coordinate point matching, the three-dimensional coordinate points in the unrecognizable area are first deleted, reducing the impact of the unrecognizable area on the matching results. At the same time, the number of three-dimensional coordinate points in the second three-dimensional coordinate point set is adjusted to the standard value, while ensuring the robot positioning accuracy, reducing the amount of calculation and improving the matching speed and efficiency.

[0137] Specifically, after step 15, the method further includes:

[0138] Step 16: determine whether there is a second obstacle in the acquisition area. If not, delete the unrecognizable area in the second storage module. If yes, proceed to step 17.

[0139] Step 17: Obtain the contour and the fifth position of the second obstacle, and extract the blocked portion of the second three-dimensional coordinate point set blocked by the second obstacle based on the contour and the fifth position.

[0140] Step 18: Obtain the three-dimensional outline corresponding to the blocked part, and define the area surrounded by the three-dimensional outline as an unrecognizable area.

[0141] The second obstacle may be the first obstacle or may not be the first obstacle; there may be one or more second obstacles.

[0142] Exemplarily, when the second obstacle enters the collection area of ​​the data collection device, the object X is located directly behind the second obstacle. The second obstacle first blocks the left half of the object X, and the left half of the object X is extracted as an unrecognizable area. As the second obstacle moves, the blocked part moves from the left half to the middle part, and then to the right half, and the middle part and the right half are extracted as unrecognizable areas in turn. After the second obstacle moves out of the collection area of ​​the data collection device, it will not block the object X, and there will be no unrecognizable area.

[0143] Figure 5 FIG. 1 is a schematic diagram of a structure of an embodiment of a multi-dimensional geographic information driven robot intelligent control system provided by the present invention. Figure 5 As shown, the system includes: a calculation control unit, a positioning module and a data receiving module, and the calculation control unit includes a first calculation module, a direction control module, a route planning module and a walking control module.

[0144] The positioning module is used to obtain a first position of the robot, wherein the first position is a three-dimensional coordinate of the robot positioning module.

[0145] The first calculation module is used to obtain the first coordinate of the center position of the first functional component of the robot head according to the first position.

[0146] The data receiving module is used to collect the second coordinate of the center point of the target object.

[0147] The orientation control module is also used to obtain a straight line connecting the first coordinate and the second coordinate, and control the rotation of the robot head based on the straight line so that the center position of the first functional component focuses on and locks the target object.

[0148] The first calculation module is further used to determine a key point for observing the target object according to the second coordinates, and obtain a second position of the key point.

[0149] The route planning module is used to plan the travel direction and driving route of the robot according to the first position and the second position.

[0150] Walking control module, used to control the robot to move to key points.

[0151] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0152] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0153] The above-mentioned embodiments only express the preferred implementation mode of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A robot intelligent control method driven by multi-dimensional geographic information, characterized in that: The steps include: Step 1: Obtain a first position of the robot, and obtain a first coordinate of a center position of a first functional component of the robot head based on the first position, wherein the first position is a three-dimensional coordinate of a robot positioning module; Step 2: collecting the second coordinates at the center point of the target object, obtaining a straight line connecting the first coordinates and the second coordinates, and controlling the rotation of the robot head based on the straight line so that the center position of the first functional component is focused and locked on the target object; Step 3: determining a key point for observing the target object based on the second coordinates, and obtaining a second position of the key point; Step 4: planning the travel direction and route of the robot based on the first position and the second position, and controlling the robot to move to the key point; In the step 2, controlling the rotation of the robot head based on the straight connecting line includes: Acquire in real time a first straight line at the center of the first functional component where the front side faces, and calculate a horizontal angle between the first straight line and a line connecting the straight lines, and a vertical angle between the first straight line and a line connecting the straight lines; The robot head is controlled to rotate based on the horizontal angle and the vertical angle.

2. The method according to claim 1, characterized in that The target object is a person, a vehicle, or an object.

3. The method according to claim 1, characterized in that In step 4, during the process of controlling the robot to move to the key point, if a first obstacle is detected in the target area in the driving direction of the robot, the following operations are performed: Step 41: obtaining a third position and a first speed of the robot at a current moment, and obtaining a fourth position and a second speed of the first obstacle, wherein the current moment is a moment when the first obstacle is detected; Step 42: judging whether the robot will collide with the first obstacle based on the third position, the first speed, the fourth position and the second speed; if not, continuing to travel along the travel route at the first speed; if yes, proceeding to step 43; Step 43, calculating a first encounter time when the distance between the bottom center point of the robot and the bottom center point of the first obstacle is a first preset distance and a first encounter position of the first obstacle; Step 44: Generate a first-category driving route and a second-category driving route based on the first encounter time and the first encounter position, respectively, wherein the first-category driving route is a newly planned route traveling at the first speed, and the second-category driving route is a newly planned route traveling at a speed different from the first speed; Step 45: Obtain a new driving route from the first type of driving routes and the second type of driving routes according to a preset rule, and control the robot to drive according to the new driving route.

4. The method according to claim 3, characterized in that In step 44, generating the first type of driving route includes the following steps: Step 4411, extracting a connecting line between the third position and the second position, and defining a straight line passing through the first meeting position and perpendicular to the connecting line as a first reference line; Step 4412: setting two adjustment nodes on the first reference line at the first preset distance from the first encounter position, defining the adjustment node close to the first obstacle as a first adjustment node, and defining the adjustment node far from the first obstacle as a second adjustment node; Step 4413: define a straight line passing through a reference node and parallel to the connecting line as a second reference line, set a point located on the second reference line, close to the robot, and at a second preset distance from the reference node as a third adjustment node, and set a point located on the second reference line, close to the key point, and at a third preset distance from the reference node as a fourth adjustment node, wherein the reference node is the first adjustment node or the second adjustment node; Step 4414: setting a point on the driving route that is a fourth preset distance vertically away from the fourth adjustment node as a fifth adjustment node, and then generating a first-type reference driving route based on the third position, the position of the third adjustment node, the position of the reference node, the position of the fourth adjustment node, the position of the fifth adjustment node, and the driving route; Step 4415: When the reference node is the second adjustment node, proceed to step 4416; when the reference node is the first adjustment node, proceed to step 4418; Step 4416: Calculate the adjustment time for the robot to reach the reference node, and calculate the time difference between the adjustment time and the first encounter time, and determine whether the time difference is within a preset range. If so, define the first type of reference driving route as the first type of driving route. If not, proceed to step 4417. Step 4417: based on the first type of reference driving route, repeat step 43 to calculate a new first encounter time and a new first encounter position, then repeat step 4411, and then set a new second adjustment node on the first reference line on the side of the connecting line away from the first obstacle, and then repeat steps 4413 to 4417; Step 4418: Based on the first type of reference driving route, determine whether the robot and the first obstacle will collide; if not, proceed to step 4419; if yes, proceed to step 4420; Step 4419: on the first reference line, a new first adjustment node is set at a position that is located on the side of the first adjustment node away from the first obstacle and at a fifth preset distance from the first adjustment node, and steps 4413 to 4414 are repeated. Then, based on the first type of reference driving route, it is determined whether the robot and the first obstacle will collide. If not, step 4419 is repeated. If yes, the first type of reference driving route at the time of the last determination that there will be no collision is defined as the first type of driving route. Step 4420: Based on the first type of reference driving route, repeat step 43 to calculate a new first encounter time and a new first encounter position, then repeat step 4411, and then set a new first adjustment node on the first reference line on the side of the connecting line close to the first obstacle, and then repeat steps 4413 to 4415, and steps 4418 to 4420.

5. The method according to claim 4, characterized in that In step 44, generating the second type of driving route includes the following steps: Step 4421, extracting a connecting line between the third position and the second position, and defining a straight line passing through the first meeting position and perpendicular to the connecting line as a first reference line; Step 4422: Generate a third reference line with the fourth position as an endpoint and the travel direction of the first obstacle as an extension direction, then set N1 second meeting positions on the third reference line close to the first obstacle and set N2 second meeting positions on the first reference line away from the first obstacle at intervals of a sixth preset distance with the first meeting position as a reference point; Step 4423: Generate two second-category reference driving routes for the first meeting position and any second meeting position according to the method of steps 4412 to 4414, then delete duplicate routes to obtain the second-category driving route; Step 4424: For any second-type driving route, control the robot to change speed between the third position and the third adjustment node, and drive at a constant speed according to the first speed after passing the third adjustment node, so that the time when the robot reaches the reference node is the same as the time when the first obstacle reaches the meeting position, wherein the meeting position is the first meeting position or the second meeting position.

6. The method according to claim 3, characterized in that In step 45, the driving routes that the robot cannot pass through in the first type of driving routes and the second type of driving routes are deleted to obtain a set of pending driving routes, and then the movement cost of each pending driving route is calculated, and the pending driving route with the smallest movement cost is used as the new driving route. The calculation formula of the movement cost is: ， Among them, C i is the travel cost of the i-th undetermined travel route, α1 and α2 are parameter weight coefficients, S i is the total length of the i-th pending driving route, T i is the time taken to reach the second location via the i-th pending driving route.

7. The method according to claim 1 or 3, characterized in that: The robot position acquisition methods include: Step 11: Obtain the estimated position of the robot and a first three-dimensional coordinate point set collected by a data acquisition device; Step 12: Based on the estimated position and the collection range of the data collection device, calculate the collection area corresponding to the first three-dimensional coordinate point set, and obtain a second three-dimensional coordinate point set from a first storage module based on the collection area, wherein the first storage module stores a standard three-dimensional coordinate point set of the area where the robot is located; Step 13, determining whether the second storage module stores an unrecognizable area, if yes, deleting the three-dimensional coordinate point corresponding to the unrecognizable area from the second three-dimensional coordinate point set, generating a new second three-dimensional coordinate point set, and then proceeding to step 14, if no, directly proceeding to step 14; Step 14, calculating the total number of three-dimensional coordinate points in the second three-dimensional coordinate point set, and determining whether the total number is equal to the standard value. If so, directly proceeding to step 15; if not, adding or deleting the second three-dimensional coordinate point set to generate a third three-dimensional coordinate point set, wherein the number of three-dimensional coordinate points in the third three-dimensional coordinate point set is equal to the standard value; Step 15: Match the first three-dimensional coordinate point set and the reference three-dimensional coordinate point set, and then adjust the estimated position based on the matching result to obtain the robot position, wherein the reference three-dimensional coordinate point set is the second three-dimensional coordinate point set or the third three-dimensional coordinate point set.

8. The method according to claim 7, characterized in that After step 15, the following steps are further included: Step 16, determining whether there is a second obstacle in the acquisition area, if not, deleting the unrecognizable area in the second storage module, if yes, proceeding to step 17; Step 17: acquiring the contour and the fifth position of the second obstacle, and extracting the blocked portion of the second three-dimensional coordinate point set blocked by the second obstacle based on the contour and the fifth position; Step 18: Obtain a three-dimensional outline corresponding to the blocked portion, and define an area surrounded by the three-dimensional outline as the unrecognizable area.

9. A robot intelligent control system driven by multi-dimensional geographic information, used to implement the method according to any one of claims 1 to 8, characterized in that: include: A calculation control unit, a positioning module and a data receiving module, wherein the calculation control unit includes a first calculation module, a direction control module, a route planning module and a walking control module; The positioning module is used to obtain a first position of the robot, wherein the first position is a three-dimensional coordinate of the robot positioning module; The first calculation module is used to obtain the first coordinate of the center position of the first functional component of the robot head according to the first position; The data receiving module is used to collect the second coordinates of the center point of the target object; The orientation control module is further used to obtain a straight line connecting the first coordinate and the second coordinate, and control the rotation of the robot head based on the straight line so that the center position of the first functional component is focused and locked on the target object; The first calculation module is further used to determine a key point for observing the target object according to the second coordinates, and obtain a second position of the key point; The route planning module is used to plan the travel direction and travel route of the robot according to the first position and the second position; The walking control module is used to control the robot to move to the key point; The controlling the rotation of the robot head based on the straight connecting line comprises: Acquire in real time a first straight line at the center of the first functional component where the front side faces, and calculate a horizontal angle between the first straight line and a line connecting the straight lines, and a vertical angle between the first straight line and a line connecting the straight lines; The robot head is controlled to rotate based on the horizontal angle and the vertical angle.

Images