CN114326710A - Robot, robot driving strategy determination method, device and storage medium - Google Patents
Robot, robot driving strategy determination method, device and storage medium Download PDFInfo
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Abstract
The application relates to a robot, a robot driving strategy determination method, a robot driving strategy determination device and a storage medium. The method comprises the steps that when the robot moves according to a planned initial driving strategy, the acceleration value of the robot in the current path section is obtained; comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section; and if the current path section is judged to be uneven, replacing the driving strategy of the current path section to express the next driving strategy of the current path section. The current road surface flatness can be determined through acceleration information in the running process of the robot, and then the running strategy of the next running current path section of the robot is changed according to the flatness of the road surface, so that the robot can stably run in the next running current path section without being limited by the environmental influence of laser radar detection and the precision influence of a visual sensor, and a better decision is made for the running strategy of the robot. And the method is simple and feasible, low in cost and easy to realize.
Description
Technical Field
The present application relates to the field of robotics, and in particular, to a robot, a method and an apparatus for determining a driving strategy of the robot, and a storage medium.
Background
With the development of the robot technology, more and more robots enter our lives, for example, a meal delivery robot, a floor sweeping robot and the like bring convenience to our lives.
When a common mobile service robot runs, a depth camera, a vision sensor or a laser radar is usually used to determine the flatness of the ground.
However, the prior art is limited by the environmental influence of laser radar detection and the precision influence of a vision sensor, so that the prior art has the problem that the road condition is difficult to accurately judge.
Disclosure of Invention
Therefore, it is necessary to provide a robot capable of accurately determining a road condition, a method and an apparatus for determining a driving strategy of the robot, and a storage medium for the robot.
A robot comprising a memory and a processor, the memory having stored therein computer-readable instructions executable on the processor, the processor when executing the computer-readable instructions effecting the steps of:
when the robot moves according to the planned initial driving strategy, acquiring an acceleration value of the robot in the current path segment;
comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section;
and if the current path section is judged to be uneven, determining the latest driving strategy of the current path section according to the size relation between the acceleration value and the preset threshold range, and replacing the initial driving strategy with the latest driving strategy to be used as the driving strategy of the robot at the current path section next time.
In one embodiment, the comparing the acceleration value with a preset threshold range for determining the flatness degree of the current path segment includes:
if the acceleration value is smaller than the minimum value of the preset threshold range, judging that the ground flatness of the current path section is flat;
and if the acceleration value is larger than or equal to the minimum value of the preset threshold range, judging that the ground flatness of the current path section is uneven.
In one embodiment, if the acceleration value is greater than or equal to the minimum value of the preset threshold, the leveling degree of the ground of the current path segment is uneven, including:
if the acceleration value is within the preset threshold range, judging that the unevenness degree is slight unevenness;
and if the acceleration value is larger than or equal to the maximum value of the preset threshold range, judging that the unevenness degree is very unevenness.
In one embodiment, the generating the latest driving strategy of the current path segment according to the magnitude relation between the acceleration value and the preset threshold range includes:
if the acceleration value is within the preset threshold range, the latest driving strategy of the current path section is deceleration driving;
and if the acceleration value is larger than or equal to the maximum value of the preset threshold range, the latest driving strategy of the current path segment is bypassing driving.
In one embodiment, the driving strategy includes an operating state of the robot in the current path segment, and the operating state is uniform speed driving, deceleration driving, acceleration driving or detour driving.
In one embodiment, the obtaining an acceleration value of the robot at the current path segment when the robot moves according to the planned initial driving strategy includes:
when the robot moves according to the planned initial driving strategy, acquiring the real-time acceleration of each position node of the robot in the current path segment;
and adding and averaging the real-time acceleration of each position node to obtain the acceleration value of the robot in the current path segment.
In one embodiment, the obtaining an acceleration value of the robot at the current path segment when the robot moves according to the planned initial driving strategy includes:
when the robot moves according to the planned initial driving strategy, acquiring the acceleration change rate of each position node of the robot in the current path segment;
and performing linear fitting on the acceleration change rate of each position node, and obtaining the acceleration value of the robot in the current path section according to the slope of a straight line generated after the linear fitting.
In a second aspect, the present application provides a method for determining a driving strategy of a robot, the method including:
when the robot moves according to the planned initial driving strategy, acquiring an acceleration value of the robot in the current path segment;
comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section;
if the current path section is judged to be uneven, determining the latest driving strategy of the current path section according to the magnitude relation between the acceleration value and the preset threshold range, and replacing the initial driving strategy with the latest driving strategy to serve as the driving strategy of the robot at the current path section next time
In a third aspect, the present application provides a robot travel strategy determination device, comprising:
the acquisition module is used for acquiring the acceleration value of the robot in the current path segment when the robot moves according to the planned initial driving strategy;
the judging module is used for comparing the acceleration value with a preset threshold range and judging the flatness degree of the current path section;
an updating module, configured to determine a latest driving strategy of the current path segment according to a magnitude relationship between the acceleration value and the preset threshold range if the current path segment is determined to be uneven, and replace the initial driving strategy with the latest driving strategy to serve as a driving strategy of the robot at the current path segment next time
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program for implementing the steps of the method in the embodiment of the second aspect described above when executed by a processor.
According to the robot, the method and the device for determining the robot driving strategy and the storage medium, when the robot moves according to the planned initial driving strategy, the acceleration value of the robot on the current path section is obtained; comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section; and if the current path section is judged to be uneven, determining the latest driving strategy of the current path section according to the size relation between the acceleration value and the preset threshold range, and replacing the initial driving strategy with the latest driving strategy to be used as the driving strategy of the robot at the path section next time. The method and the device can determine the current road surface flatness degree through the acceleration information in the running process of the robot, and further change the running strategy in real time according to the flatness degree of the road surface, so that the robot can stably run at the current path section when running next time, and is not limited by the environmental influence of laser radar detection and the precision influence of a visual sensor, and better makes a decision for the running strategy of the robot. And the method is simple and feasible, low in cost and easy to realize.
Drawings
FIG. 1 is a block diagram of the internal structure of a robot in one embodiment;
FIG. 2 is a schematic flow chart diagram illustrating execution of computer readable instructions by a robot in one embodiment;
FIG. 2-a is a schematic diagram of a robot autonomous driving route;
FIG. 2-b is a schematic view of the acceleration of the robot traveling on different roads;
FIG. 2-c is a schematic view of the robot passing over an uneven road surface;
FIG. 2-d is a schematic illustration of the robot slowing down through;
FIG. 2-e is a schematic diagram of the robot passing around;
FIG. 3 is a schematic flow chart of another embodiment of a robot executing computer readable instructions;
fig. 4 is a block diagram showing the construction of a robot running strategy determining apparatus according to an embodiment;
fig. 5 is a block diagram showing the construction of a robot travel strategy determination apparatus according to another embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Fig. 1 is a schematic diagram of a robot, which may be a server in this embodiment. The robot includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the robot is used to provide computational and control capabilities. The storage of the robot comprises a nonvolatile storage medium and an internal storage. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the robot is used to store driving strategies. The network interface of the robot is used for communicating with an external terminal through network connection. The computer program is executed by a processor to implement a method for determining a driving strategy for a robot.
Those skilled in the art will appreciate that the configuration shown in fig. 1 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation on the robot to which the present application may be applied, and that a particular robot may include more or fewer components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, as shown in fig. 1, there is provided a robot, the robot comprising a memory and a processor, the memory storing computer readable instructions executable on the processor, the processor implementing the following steps as shown in fig. 2 when executing the computer readable instructions:
s202, when the robot moves according to the planned initial driving strategy, the acceleration value of the robot on the current path segment is obtained.
The planned initial driving strategy may include, without limitation, a system default driving strategy or a strategy adopted in the last robot movement. For example, the speed is constant, the acceleration is accelerated, the deceleration is decelerated, the detour is performed, and the like, but not limited thereto. When the robot runs according to a path selected after the map is built from the starting point to the end point, the path is divided into a plurality of path sections according to preset distance intervals, and the current path section where the robot runs is the current path section. Fig. 2-a is a schematic diagram of a route where the robot autonomously travels, where a is a travel path of the robot.
Specifically, the robot is provided with an acceleration sensor, and when the robot moves according to a planned initial driving strategy, acceleration information, namely acceleration values, of each position node in a current path segment can be acquired in real time. Each position node may include a position node arbitrarily selected in the current path segment, or may be a plurality of position nodes obtained by dividing the current path segment according to a preset division distance interval, which is not limited herein.
And S204, comparing the acceleration value with a preset threshold range, and judging the flatness degree of the current path section.
The ground surface may be flat, uneven, very uneven, etc., without limitation.
Specifically, the ground flatness degree of the current path segment can be determined by averaging the acceleration information of each position node; for example, the acceleration information of each position point within 10 meters of the preset driving distance is obtained, the average value is compared with a preset threshold range, then the ground flatness degree within the preset distance is determined according to the comparison result, and the acceleration and the ground flatness degree of each position node are recorded, so that the subsequent robot can compare the acceleration information and the ground flatness degree when executing tasks. In another embodiment, the slope of the straight line after fitting can be determined by means of linear fitting according to the acceleration information of each position node in the current path segment, the acceleration change rate is determined, the acceleration change rate is compared with the change rate threshold, and the ground flatness degree is determined according to the comparison result. Fig. 2-b is a schematic diagram of acceleration of the robot running on different roads, where the abscissa is the coordinate of the execution path, the ordinate is the acceleration value, C is an uneven path segment, and D is an even path segment. Comparing the acceleration value with a preset threshold range, wherein when the acceleration value is smaller than the minimum value of the preset threshold range, the current path section is determined to be smooth; when the acceleration value is within the preset threshold range, the current path section is not flat; and when the acceleration value is larger than the maximum value of the preset threshold value, the current path section is uneven. Or when the acceleration value is smaller than the minimum value of the preset threshold range, the current path section is flat; if the acceleration value is larger than the minimum value of the preset threshold range, the current path section is uneven, wherein if the acceleration value is within the preset threshold range, the current path section is slightly uneven; if the acceleration value is greater than the maximum value of the preset threshold, the current path segment is very uneven, and no limitation is imposed on the current path segment. The comparison method may be, for example, a ratio, a difference, a quotient, and the like, and is not limited herein. Wherein, fig. 2-c are schematic diagrams of the robot passing through uneven road surfaces.
And S206, if the current path section is judged to be uneven, determining the latest driving strategy of the current path section according to the magnitude relation between the acceleration value and the preset threshold range, and replacing the initial driving strategy with the latest driving strategy to represent the next driving strategy of the path section.
Specifically, if the current path segment is judged to be uneven, the latest driving strategy of the current path segment is generated according to the size relation between the acceleration value and the preset threshold range, and the latest driving strategy is replaced by the initial driving strategy to represent the next driving strategy of the current path segment. For example, if the current route segment is determined to be rough, the operation state in the driving strategy of the current route segment is updated to the decelerated driving state, that is, the next driving strategy is generated.
Optionally, the planned initial driving strategy comprises: the running state, the travel path section, the ground flatness of the travel path section, and the acceleration of the robot through the travel path section.
For example, if it is determined that the ground flatness is uneven, the latest driving strategy of the current path segment may be generated according to the magnitude relationship between the acceleration value and the preset threshold range, the initial driving strategy is replaced with the latest driving strategy, that is, the next driving strategy is a deceleration driving strategy, and the robot is driven to drive to the target point according to the updated driving strategy. When the personnel determine that the ground is very uneven, the planned running strategy can be updated to stop, and the detection is carried out again; the vehicle may also be a round-trip vehicle, which is not limited herein. Wherein, fig. 2-d are schematic diagrams of the robot passing through at a reduced speed, and fig. 2-e are schematic diagrams of the robot passing by.
In the embodiment, when the robot moves according to the planned initial driving strategy, the acceleration value of the robot on the current path segment is obtained; comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section; and if the current path section is judged to be uneven, replacing the driving strategy of the current path section to express the next driving strategy of the current path section. The current road surface flatness can be determined through acceleration information in the running process of the robot, and then the running strategy of the next running current path section of the robot is changed according to the flatness of the road surface, so that the robot can stably run in the next running current path section without being limited by the environmental influence of laser radar detection and the precision influence of a visual sensor, and a better decision is made for the running strategy of the robot. And the method is simple and feasible, low in cost and easy to realize.
The above embodiment describes the steps performed by the robot during the operation process, in which the most important is how the robot determines the smoothness of the ground on the traveling path, and now describes an embodiment, in which the acceleration value is compared with the preset threshold range for determining the smoothness of the current path segment, including:
if the acceleration value is smaller than the minimum value of the preset threshold range, the ground flatness of the current path section is flat;
and if the acceleration value is larger than or equal to the minimum value of the preset threshold range, the ground flatness in the current path section is uneven.
Specifically, if the acceleration value is smaller than the minimum value of the preset threshold range, the current path section is flat; and if the acceleration value is larger than the minimum value of the preset threshold range, the current path section is uneven. For example, the acceleration value is 1m/s, the preset threshold range is 1.5m/s-2m/s, and at this time, the average acceleration is smaller than the minimum value of the preset threshold range, and the ground flatness degree in the preset distance range is flat. If the acceleration value is within the preset threshold range, the unevenness degree of the current path section is slightly uneven; and if the acceleration value is larger than the maximum value of the preset threshold value, the unevenness degree of the current path section is very uneven. For example, the value acceleration is 1.7m/s, the acceleration threshold range is 1.5m/s-2m/s, and at this time, the acceleration value is within the preset threshold range, and the ground flatness of the current path segment is uneven. For example, the acceleration value is 2.1m/s, the preset threshold range is 1.5m/s-2m/s, and at this time, the acceleration value is greater than the maximum value of the preset threshold range, and the ground flatness within the preset distance range is very uneven.
In this embodiment, if the acceleration value is smaller than the minimum value of the preset threshold range, the ground flatness of the current path segment is flat; and if the acceleration value is larger than or equal to the minimum value of the preset threshold value, the ground flatness in the current path section is uneven. The method for comparing the acceleration value with the preset threshold range judges whether the ground of the current path section is flat or not, and makes data support for judging whether the driving strategy needs to be changed or not when the current path section is driven next time.
When the latest driving strategy is deceleration driving, the speed of deceleration driving of the robot may be determined according to a preset rule.
In one embodiment, the preset threshold range comprises a first threshold range and a second threshold range, and if the acceleration value is within the first threshold range, the speed of the deceleration running in the latest running strategy is 60% -80% of the normal running speed; and if the acceleration value is within the second threshold value range, the speed of the deceleration running in the latest running strategy is 40-50% of the normal running speed.
For example, the normal running speed of the robot is 0.8m/s, the preset threshold range is 1.5m/s-2m/s, the first threshold range is 1.5m/s-1.8m/s, and the second threshold range is 1.8m/s-2 m/s. If the acceleration value is 1.6m/s, which is within the first threshold range, the speed of the decelerated run in the latest running strategy may be 0.64 m/s; if the acceleration value is 1.9m/s, which is within the second threshold range, the speed of the decelerated run in the latest running strategy may be 0.48 m/s.
Alternatively, in one embodiment, the preset threshold range includes a first threshold range and a second threshold range, and the different threshold ranges correspond to different travel speeds.
For example, the normal running speed of the robot is 0.8m/s, and if the acceleration value is within the first threshold value range, the speed of the deceleration running in the latest running strategy is 0.6 m/s; and if the acceleration value is within the second threshold value range, the speed of the deceleration running in the latest running strategy is 0.4 m/s.
When the latest driving strategy is the detour driving, the robot can select a detour moving path according to a preset rule. For example, in one embodiment, the path of movement of the latest driving strategy is offset by 50cm-60cm to the left or right on the basis of the previous path of movement.
The above embodiment describes how the robot determines the ground flatness on the travel path, and now describes how the robot determines the acceleration value according to an embodiment, as shown in fig. 3, when the robot moves according to the planned initial travel strategy, acquiring the acceleration value of the robot in the current path segment includes:
s302, when the robot moves according to the planned initial driving strategy, the acceleration values of each position node of the robot in the current path segment are obtained.
And S304, adding and averaging the acceleration values of the nodes at each position to obtain the acceleration value of the robot at the current path segment.
Specifically, when the robot moves according to a planned initial driving strategy, acquiring an acceleration value of each position node of the robot in a current path segment; and adding and averaging the acceleration values of the nodes at the positions to obtain the acceleration value of the robot at the current path section.
In the embodiment, when the robot moves according to the planned initial driving strategy, the acceleration values of each position node of the robot in the current path segment are obtained; and adding and averaging the acceleration values of the nodes at the positions to obtain the acceleration value of the robot at the current path section. The method can accurately estimate the ground flatness degree in the current path section, is simple and effective, and is not influenced by the environment of radar test.
To facilitate understanding of those skilled in the art, the method for determining the robot driving strategy is further described in an embodiment, the robot includes a memory and a processor, the memory stores computer readable instructions executable on the processor, and the processor executes the computer readable instructions to implement the steps of:
s401, when the robot moves according to a planned initial driving strategy, acquiring an acceleration value of each position node of the robot in a current path segment; the planned initial driving strategy comprises the following steps: the running state, the travel path section, the ground flatness of the travel path section, and the acceleration of the robot through the travel path section.
S402, adding and averaging the acceleration values of the nodes at all positions to obtain the acceleration value of the robot at the current path segment.
And S403, comparing the acceleration value with a preset threshold range, and judging the flatness degree of the current path section.
S404, if the acceleration value is smaller than the minimum value of the preset threshold range, the ground flatness of the current path section is flat.
S405, if the acceleration value is within the preset threshold range, the unevenness degree is slightly unevenness.
And S406, if the acceleration value is larger than the maximum value of the preset threshold range, the degree of flatness is very uneven.
And S407, if the degree of unevenness is slight unevenness, changing the running state in the planned initial running strategy into speed reduction running to obtain the next running strategy.
And S408, if the degree of unevenness is very uneven, changing the running path in the planned initial running strategy to bypass the current path section to obtain the next running strategy.
In the embodiment, when the robot moves according to the planned initial driving strategy, the acceleration value of the robot at the current path segment is obtained; comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section; and if the current path section is judged to be uneven, replacing the driving strategy of the current path section to express the next driving strategy of the current path section. The current road surface flatness can be determined through acceleration information in the running process of the robot, and then the running strategy of the next running current path section of the robot is changed according to the flatness of the road surface, so that the robot can stably run in the next running current path section without being limited by the environmental influence of laser radar detection and the precision influence of a visual sensor, and a better decision is made for the running strategy of the robot. And the method is simple and feasible, low in cost and easy to realize.
It should be understood that although the various steps in the flow charts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
The above embodiments describe a robot, and a method for determining a robot driving strategy according to an embodiment is described, in which the method for determining a robot driving strategy includes:
when the robot moves according to the planned initial driving strategy, acquiring an acceleration value of the robot in the current path segment;
comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section;
and if the current path section is judged to be uneven, updating the driving strategy of the path section to represent the next driving strategy of the path section.
In the embodiment, when the robot moves according to the planned initial driving strategy, the acceleration value of the robot on the current path segment is obtained; comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section; and if the current path section is judged to be uneven, updating the driving strategy of the path section to represent the next driving strategy of the path section. Can go the acceleration information of in-process through the robot, confirm current road surface roughness, and then according to the roughness on road surface, change the strategy of going in real time, make the robot can stably go when going at current path section next time to needn't be subject to the environmental impact that laser radar detected, and the precision influence of visual sensor, better make the decision for the robot strategy of going. And the method is simple and feasible, low in cost and easy to realize.
In one embodiment, comparing the acceleration value with a preset threshold range for determining the flatness degree of the current path segment includes:
if the acceleration value is smaller than the minimum value of the preset threshold range, the ground flatness of the current path section is flat;
and if the acceleration value is larger than or equal to the minimum value of the preset threshold range, the ground flatness in the current path section is uneven.
In one embodiment, if the acceleration value is greater than or equal to the preset threshold range, the ground flatness of the current path segment is uneven, including:
if the acceleration value is within the preset threshold range, the degree of unevenness is slight unevenness;
if the acceleration value is greater than the maximum value of the preset threshold range, the degree of unevenness is very uneven.
In one embodiment, if the current path segment is determined to be uneven, the step of updating the driving strategy of the path segment to indicate the next driving strategy of the path segment includes:
if the degree of unevenness is slight unevenness, changing the running state in the planned initial running strategy into speed reduction running to obtain the next running strategy;
and if the degree of unevenness is very uneven, changing the running path in the planned initial running strategy to bypass the current path section to obtain the next running strategy.
In one embodiment, the planned initial driving strategy includes: the running state, the running path section, the ground flatness corresponding to the running path section and the acceleration of the robot passing through the running path section.
In one embodiment, when the robot moves according to the planned initial driving strategy, acquiring an acceleration value of the robot in the current path segment includes:
when the robot moves according to the planned initial driving strategy, acquiring acceleration values of each position node of the robot in the current path segment;
and adding and averaging the acceleration values of the nodes at the positions to obtain the acceleration value of the robot at the current path section.
For specific limitations of the method for determining the robot driving strategy, reference may be made to the above limitations of the steps implemented when a processor in the robot executes computer-readable instructions, and details are not described herein again.
The above-described embodiment describes a method for determining a robot driving strategy, and now a robot driving strategy determining apparatus is described with an embodiment, and in an embodiment, as shown in fig. 4, there is provided a robot driving strategy determining apparatus including:
the acquiring module 401 is configured to acquire an acceleration value of the robot at the current path segment when the robot moves according to the planned initial driving strategy;
a judging module 402, configured to compare the acceleration value with a preset threshold range, and configured to judge a leveling degree of the current path segment;
and an updating module 403, configured to determine a latest driving strategy of the current path segment according to a size relationship between the acceleration value and a preset threshold range if the current path segment is determined to be uneven, and replace the initial driving strategy with the latest driving strategy to serve as a driving strategy of the robot on the current path segment next time.
Optionally, the planned initial driving strategy comprises: the running state, the travel path section, the ground flatness of the travel path section, and the acceleration of the robot through the travel path section.
In the embodiment, when the robot moves according to the planned initial driving strategy, the acceleration value of the robot on the current path segment is obtained; comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section; and if the current path section is judged to be uneven, updating the driving strategy of the path section to represent the next driving strategy of the path section. Can go the acceleration information of in-process through the robot, confirm current road surface roughness, and then according to the roughness on road surface, change the strategy of going in real time, make the robot can stably go when going at current path section next time to needn't be subject to the environmental impact that laser radar detected, and the precision influence of visual sensor, better make the decision for the robot strategy of going. And the method is simple and feasible, low in cost and easy to realize.
In one embodiment, as shown in fig. 5, the determining module 402 includes:
the first determining unit 4021 is configured to determine that the ground flatness of the current path segment is flat if the acceleration value is smaller than the minimum value of the preset threshold range;
the second determining unit 4022 is configured to determine that the ground in the current path segment is uneven if the acceleration value is greater than or equal to the minimum value of the preset threshold range.
In an embodiment, the second determining unit 4022 is specifically configured to determine that the degree of unevenness is slightly uneven if the acceleration value is within a preset threshold range; if the acceleration value is greater than the maximum value of the preset threshold range, the degree of unevenness is very uneven.
In one embodiment, referring to fig. 5, the update module 403 includes:
a first updating unit 4031, configured to, if the acceleration value is within the preset threshold range, determine that the latest driving strategy of the current path segment is deceleration driving;
and a second updating unit 4032, configured to, if the acceleration value is greater than or equal to the maximum value of the preset threshold range, determine that the latest driving strategy of the current path segment is detour driving.
In one embodiment, referring to fig. 5, the obtaining module 401 includes:
the first obtaining unit 4011 is configured to obtain acceleration values of each position node of the robot in the current path segment when the robot moves according to the planned initial driving strategy;
and the averaging unit 4012 is configured to sum and average the acceleration values of the position nodes to obtain an acceleration value of the robot in the current path segment.
In an embodiment, the first obtaining unit is specifically configured to obtain an acceleration rate change of each position node of the robot in a current path segment when the robot moves according to a planned initial driving strategy; and performing linear fitting on the acceleration change rate of each position node, and obtaining the acceleration value of the robot in the current path section according to the slope of a straight line generated after the linear fitting.
For specific limitations of the robot driving strategy determining device, reference may be made to the above limitations of the robot driving strategy determining method, which are not described herein again. The modules in the robot driving strategy determination device may be implemented in whole or in part by software, hardware, or a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the robot, and can also be stored in a memory in the robot in a software form, so that the processor can call and execute operations corresponding to the modules.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A robot comprising a memory and a processor, the memory having stored therein computer-readable instructions executable on the processor, wherein the processor is configured to perform the steps of:
when the robot moves according to the planned initial driving strategy, acquiring an acceleration value of the robot in the current path segment;
comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section;
and if the current path section is judged to be uneven, determining the latest driving strategy of the current path section according to the size relation between the acceleration value and the preset threshold range, and replacing the initial driving strategy with the latest driving strategy to be used as the driving strategy of the robot at the current path section next time.
2. The robot of claim 1, wherein said comparing said acceleration value with a preset threshold range for determining a flatness level of said current path segment comprises:
if the acceleration value is smaller than the minimum value of the preset threshold range, judging that the ground flatness of the current path section is flat;
and if the acceleration value is larger than or equal to the minimum value of the preset threshold range, judging that the ground flatness of the current path section is uneven.
3. The method according to claim 2, wherein if the acceleration value is greater than or equal to the minimum value of the preset threshold, the ground level of the current path segment is uneven, and the method comprises:
if the acceleration value is within the preset threshold range, judging that the unevenness degree is slight unevenness;
and if the acceleration value is larger than or equal to the maximum value of the preset threshold range, judging that the unevenness degree is very unevenness.
4. The robot of claim 2, wherein said determining the latest driving strategy for the current path segment based on the magnitude relationship of the acceleration value to the preset threshold range comprises:
if the acceleration value is within the preset threshold range, the latest driving strategy of the current path section is deceleration driving;
and if the acceleration value is larger than or equal to the maximum value of the preset threshold range, the latest driving strategy of the current path segment is bypassing driving.
5. The robot of claim 1, wherein the driving strategy comprises an operating state of the robot at the current path segment, and the operating state is a uniform speed driving, a deceleration driving, an acceleration driving, or a detour driving.
6. The robot of claim 1, wherein said obtaining an acceleration value of the robot at a current path segment while the robot is moving according to a planned initial driving strategy comprises:
when the robot moves according to the planned initial driving strategy, acquiring the real-time acceleration of each position node of the robot in the current path segment;
and adding and averaging the real-time acceleration of each position node to obtain the acceleration value of the robot in the current path segment.
7. The robot of claim 1, wherein said obtaining an acceleration value of the robot at a current path segment while the robot is moving according to a planned initial driving strategy comprises:
when the robot moves according to the planned initial driving strategy, acquiring the acceleration change rate of each position node of the robot in the current path segment;
and performing linear fitting on the acceleration change rate of each position node, and obtaining the acceleration value of the robot in the current path section according to the slope of a straight line generated after the linear fitting.
8. A method for determining a driving strategy of a robot, the method comprising:
when the robot moves according to the planned initial driving strategy, acquiring an acceleration value of the robot in the current path segment;
comparing the acceleration value with a preset threshold range for judging the flatness degree of the current path section;
and if the current path section is judged to be uneven, determining the latest driving strategy of the current path section according to the size relation between the acceleration value and the preset threshold range, and replacing the initial driving strategy with the latest driving strategy to be used as the driving strategy of the robot at the current path section next time.
9. A robot travel strategy determination apparatus, characterized in that the apparatus comprises:
the acquisition module is used for acquiring the acceleration value of the robot in the current path segment when the robot moves according to the planned initial driving strategy;
the judging module is used for comparing the acceleration value with a preset threshold range and judging the flatness degree of the current path section;
and the updating module is used for determining the latest driving strategy of the current path section according to the magnitude relation between the acceleration value and the preset threshold range if the current path section is judged to be uneven, and replacing the initial driving strategy with the latest driving strategy to be used as the driving strategy of the robot at the current path section next time.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, is adapted to carry out the steps of the robot driving strategy determination method according to claim 8.
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