CN111123947A - Robot traveling control method and device, electronic device, medium, and robot - Google Patents
Robot traveling control method and device, electronic device, medium, and robot Download PDFInfo
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Abstract
The embodiment of the invention relates to the field of mobile robots, and discloses a method and a device for controlling the advance of a robot, electronic equipment, a medium and the robot. In the invention, a target reference point for indicating a local traveling target of the robot is determined in a pre-stored global path; generating a plurality of simulation tracks according to a plurality of groups of sampling linear speeds and sampling angular speeds of the robot; the track lengths of the plurality of simulation tracks are greater than or equal to the distance between the robot and the target reference point; determining a target simulation track in the generated multiple simulation tracks according to the position relation between each simulation track and the obstacle and the position relation between each simulation track and the pre-stored global path; and adjusting the traveling linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track, so that the robot can safely and efficiently bypass the obstacle.
Description
Technical Field
The embodiment of the invention relates to the field of mobile robots, in particular to a method and a device for controlling the advance of a robot, electronic equipment, a medium and the robot.
Background
With the rapid development of computer technology, sensor technology and artificial intelligence, the autonomous navigation technology of the robot has also made great progress, and the robot needs to perform global planning on the autonomously navigated field before performing autonomous navigation in the field. Since the position of the obstacle in the field may change, it is necessary for the robot to plan the local path to be traveled again in the process of navigating according to the globally planned path, and to control the traveling route of the robot through the planned local path, so as to avoid the robot from rubbing against the obstacle with a changed position.
Usually, a local path of the robot can be planned through a dynamic window algorithm (dwa algorithm), firstly, a plurality of groups of linear velocities and angular velocities are set, a plurality of simulation tracks are generated according to the linear velocities and the angular velocities, finally, the plurality of simulation tracks are scored through a scoring function, the simulation track with the highest score is selected as a local traveling route of the robot, and the robot is controlled to travel according to the simulation track with the highest score.
The inventors found that at least the following problems exist in the related art: when an obstacle exists near the robot to block the traveling route of the robot, the simulation track with the highest score calculated by the dynamic window algorithm is generally a straight-line path which is low in speed and faces the obstacle as shown in fig. 1, the robot travels along the simulation track and finally stops near the obstacle, and for the robot with an inflexible chassis, the robot cannot safely bypass the obstacle without changing the posture of the robot.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a device for controlling the robot to travel, electronic equipment, a medium and a robot, so that the robot can safely and efficiently bypass obstacles.
In order to solve the above technical problem, an embodiment of the present invention provides a method for controlling robot traveling, including: determining a target reference point for indicating a local traveling target of the robot in a pre-stored global path; generating a plurality of simulation tracks according to a plurality of groups of sampling linear speeds and sampling angular speeds of the robot; the track lengths of the plurality of simulation tracks are greater than or equal to the distance between the robot and the target reference point; determining a target simulation track in the generated multiple simulation tracks according to the position relation between each simulation track and the obstacle and the position relation between each simulation track and the pre-stored global path; and adjusting the traveling linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track.
An embodiment of the present invention further provides a robot traveling control apparatus, including: the system comprises a target reference point determining module, an obtaining module, a generating module, a target simulation track determining module and an adjusting module; the target reference point determining module is used for determining a target reference point for indicating a local traveling target of the robot in a pre-stored global path; the acquisition module is used for acquiring a plurality of groups of sampling linear speeds and sampling angular speeds of the robot; the generating module is used for correspondingly generating a plurality of simulation tracks according to the plurality of groups of sampling linear speeds and sampling angular speeds, and the track lengths of the plurality of simulation tracks are greater than or equal to the distance between the robot and a target reference point; the target simulation track determining module is used for determining a target simulation track in the generated multiple simulation tracks according to the position relation between each simulation track and the barrier and the position relation between each simulation track and the pre-stored global path; the adjusting module is used for adjusting the linear speed and the angular speed of the robot according to the sampling linear speed and the sampling angular speed corresponding to the target simulation track.
An embodiment of the present invention also provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform a method of controlling the travel of the robot.
An embodiment of the present invention further provides a storage medium storing a computer program, wherein the computer program is executed by a processor to control the robot to travel.
The embodiment of the invention also provides a robot, which at least comprises the electronic equipment.
Compared with the prior art, the embodiment of the invention selects the position coordinates in the pre-stored global path at a distance in front of the current position of the robot as the target reference points of the currently planned local path. The method comprises the steps that a plurality of simulation tracks are correspondingly generated according to a plurality of groups of acquired sampling linear speeds and sampling angular speeds of the robot, the generated simulation tracks are larger than or equal to the distance between the robot and a target reference point, the track length is set, so that the simulation tracks which cannot bypass the obstacle can be coincided with the position of the obstacle to a certain extent, when the target simulation track is determined according to the position relation between each simulation track and the obstacle and the position relation between the simulation track and a pre-stored global path, the simulation track which cannot bypass the obstacle cannot be used as the finally determined target simulation track, and the finally determined target simulation track can be ensured to smoothly bypass the obstacle without adjusting the pose of the robot in the advancing process. After the target simulation track is determined, the advancing linear velocity and the angular velocity of the robot are adjusted to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track, so that the robot can bypass the obstacle according to the determined target simulation track, and the advancing safety of the robot is guaranteed.
In addition, the multiple sets of sampling linear velocities and sampling angular velocities of the robot are obtained by: determining the value range of the curvature radius of the simulation track according to the value range of the simulation linear velocity and the value range of the simulation angular velocity of the robot in the simulation time; according to the value range of the curvature radius, obtaining a plurality of curvature radii with different values as sampling curvature radii; and respectively calculating to obtain a plurality of groups of corresponding sampling linear velocities and sampling angular velocities according to the plurality of sampling curvature radii. The curvature radii with different numerical values respectively determine a group of sampling linear velocities and sampling angular velocities, each group of sampling linear velocities and sampling angular velocities correspondingly generate a simulation track, and a plurality of simulation tracks generated in the way are not overlapped, so that overlapped invalid tracks are avoided being generated, and the efficiency of generating the simulation tracks is improved.
In addition, according to a plurality of sampling curvature radiuses, respectively calculating to obtain a plurality of groups of corresponding sampling linear velocities and sampling angular velocities, the method comprises the following steps: calculating sampling linear speeds corresponding to the sampling curvature radii by utilizing a speed drop function through the preset maximum value and minimum value of the linear speeds, the preset maximum value of the curvature radii, the maximum value of the sampling linear speeds and the sampling curvature radii; and calculating to obtain the sampling angular velocity corresponding to the sampling curvature radius according to the sampling curvature radius and the corresponding sampling linear velocity. The sampling linear velocity calculated through the speed drop function can regularly generate the sampling linear velocity according to the size of the numerical value of the curvature radius, so that the robot has higher speed on a linear track line, and reduces the linear velocity according to the bending degree during turning, thereby ensuring that the robot can efficiently and safely advance.
In addition, according to the value range of the curvature radius, the curvature radius of a plurality of different values is obtained as the sampling curvature radius, and the method comprises the following steps: sampling the numerical value in the value range of the curvature radius by using a preset sampling stepping value; the radius of curvature of the sampled value is taken as the sampling radius of curvature. Therefore, the generated simulation track can be an ordered track, and the subsequent debugging of the generation algorithm of the simulation track is facilitated.
In addition, determining a target simulation track in the generated multiple simulation tracks according to the position relationship between each simulation track and the obstacle and the position relationship between each simulation track and the pre-stored global path, includes: generating a scoring function according to the position information of the barrier and a pre-stored global path; scoring the generated plurality of simulation tracks through the generated scoring function respectively; and taking the simulation track with the highest score as a target simulation track. The process of selecting the target simulation track from the multiple simulation tracks is simpler and more convenient through the scoring function.
In addition, the chassis of the robot comprises an Ackerman body chassis or a two-wheel differential body chassis.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
FIG. 1 is a schematic illustration of a simulation trace generated according to the prior art;
FIG. 2 is a schematic diagram of a simulation trace generated in accordance with a first embodiment of the present invention;
fig. 3 is a flowchart of a control method of robot traveling according to a first embodiment of the present invention;
fig. 4 is a flowchart of a control method of robot traveling according to a second embodiment of the present invention;
fig. 5 is a schematic configuration diagram of a control apparatus for robot traveling according to a third embodiment of the present invention;
fig. 6 is a schematic configuration diagram of a control apparatus for robot traveling according to a fourth embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device in a fifth embodiment according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that in various embodiments of the invention, numerous technical details are set forth in order to provide a better understanding of the present application. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
The following embodiments are divided for convenience of description, and should not constitute any limitation to the specific implementation manner of the present invention, and the embodiments may be mutually incorporated and referred to without contradiction.
A first embodiment of the present invention relates to a method of controlling robot travel, including: determining a target reference point for indicating a local traveling target of the robot in a pre-stored global path; generating a plurality of simulation tracks according to a plurality of groups of sampling linear speeds and sampling angular speeds of the robot; the track lengths of the plurality of simulation tracks are greater than or equal to the distance between the robot and the target reference point; determining a target simulation track in the generated multiple simulation tracks according to the position relation between each simulation track and the obstacle and the position relation between each simulation track and the pre-stored global path; and adjusting the traveling linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track. The following describes the implementation details of the control method for robot traveling according to the present embodiment, and the following description is only provided for the sake of understanding, and is not necessary to implement the present embodiment.
As shown in fig. 3, a first embodiment relates to a method for controlling robot traveling, including:
Specifically, the robot needs to perform global planning on the autonomously navigated field before performing autonomous navigation in the field. The tester controls the robot to advance in the field in advance and records the position information of the obstacles in the field, or the tester directly introduces a point cloud map of the field into a memory of the robot. After the position information of all the obstacles in the field is acquired, the robot plans a global travel route under the field to generate a global path. And planning a local traveling path on the basis of a global path which needs to be prestored when the robot autonomously navigates. The robot determines the position of the robot in the point cloud map of the global path according to the position information of the robot, and determines a position on the path in front of the position of the robot in the global path, wherein the determined position is a target reference point and is used for indicating a local traveling target of the robot. For example, a position on the global path one meter away from the current position of the robot may be selected as the target reference point, and the manner of selecting the target reference point is not limited herein.
And 302, correspondingly generating a plurality of simulation tracks according to a plurality of groups of sampling linear speeds and sampling angular speeds of the robot.
Specifically, when the linear velocity and the angular velocity of the robot are determined, the travel trajectory of the robot can be determined. Therefore, when the simulation track is generated, a plurality of groups of sampling linear velocities and sampling angular velocities can be obtained, a plurality of simulation tracks are correspondingly generated according to the plurality of groups of sampling linear velocities and sampling angular velocities, the generated plurality of simulation tracks are shown in fig. 2, the track lengths of the generated plurality of simulation tracks are larger than or equal to the distance between the robot and the target reference point, and the track lengths of the generated plurality of simulation tracks can be set to be the same fixed value in practical application, so that the complexity of the operation of generating the simulation tracks is simplified. The length of the track for generating the simulation track can be set to ensure that the generated simulation track can have a part which is overlapped with the position of the obstacle when the generated simulation track cannot bypass the obstacle, so that the finally determined target simulation track can bypass the obstacle. When the local path is planned, if an obstacle influences the traveling of the robot, the position of the obstacle is between the robot and the target reference point, and the distance between the robot and the obstacle is shorter than the distance between the robot and the target reference point, so that a simulation track with the track length larger than or equal to the distance between the robot and the target reference point is generated, and the simulation track which is not overlapped with the position of the obstacle can be ensured to safely bypass the obstacle.
In addition, the obtained multiple groups of sampling linear velocities and sampling angular velocities can be selected in a value range in a random mode, and the sampling linear velocities and the sampling angular velocities can also be obtained by calculation according to the sampling curvature radius. The sampling linear velocity and the sampling angular velocity are obtained through sampling curvature radius calculation, and the curvature radius can represent the radian of the track, and the radians of the corresponding tracks are different when the curvature radius values are different, so that the plurality of generated simulation tracks do not have coincident simulation tracks, and the effectiveness of the generated simulation tracks is ensured.
And step 303, determining a target simulation track in the generated multiple simulation tracks according to the position relationship between each simulation track and the obstacle and the position relationship between each simulation track and the pre-stored global path.
After a plurality of simulation tracks are generated, the simulation tracks with the overlapped parts with the positions of the obstacles can be eliminated, and the robot can pass through the positions of the obstacles according to the simulation tracks with the overlapped parts with the positions of the obstacles, so that the robot can be rubbed and collided with the obstacles. In addition, the simulation track with the highest path matching degree between the robot and the target reference point in the plurality of simulation tracks and the pre-stored global path can be used as the target simulation track, so that the robot can be ensured to safely bypass the obstacle on the premise of changing the traveling speed of the robot to the minimum extent.
In addition, the target simulation track can be selected according to the distances between the end points of the multiple simulation tracks and the target reference point, the target simulation track can be selected according to various selection conditions such as the direction and the size of the linear velocity and the angular velocity of the robot, the selection condition of the target simulation track is set according to the requirements of a user in practical application, for example, the target simulation track with the closest distance to the target reference point can be selected to ensure the high efficiency of the robot in traveling; in order to ensure the safety of the robot in the process of traveling, a simulation track with a certain distance from the position of the obstacle is selected as a target simulation track, and the like. In order to synthesize the selection conditions of the multiple target simulation tracks, a scoring function can be generated according to the multiple selection conditions in the description, each simulation track is scored through the scoring function, and the simulation track with the highest score is used as the target simulation track, so that the determination of the target simulation track is more efficient.
And 304, adjusting the traveling linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track. Specifically, after the target simulation track is determined, a sampling linear velocity and a sampling angular velocity corresponding to the target simulation track are obtained, whether the sampling linear velocity and the sampling angular velocity are the same as the current advancing linear velocity and the current advancing angular velocity of the robot or not is judged, and if the sampling linear velocity and the sampling angular velocity are the same as the current advancing linear velocity and the current advancing angular velocity of the robot, the advancing linear velocity and the advancing angular velocity of the robot do not need to be adjusted; if the linear velocity and the angular velocity are different, the current linear velocity and the current angular velocity of the robot are adjusted, the adjusted values of the linear velocity and the angular velocity are the values of the sampling linear velocity and the sampling angular velocity, the adjustment of the advancing track of the robot can be realized by controlling the values of the linear velocity and the angular velocity when the robot advances, the robot is controlled to advance along the target simulation track, and the planning of the local path of the robot is completed once.
In addition, after the local path of the robot is planned once and in the process of traveling according to the planned local path, the local path of the robot can be planned again, so that the traveling route of the robot is continuously perfected, and the robot can efficiently and safely travel in a field. The period of the robot local path planning may be determined according to the algorithm of the generated simulation trajectory, may also be preset, and may also be adjusted according to the condition of the robot traveling, for example, after the robot local path planning is performed for a plurality of times continuously, the traveling speed of the robot does not need to be adjusted, the value of the period may be appropriately increased, otherwise, the value of the period may be appropriately decreased if the value of the adjustment of the traveling speed for a plurality of times is large, so that the robot may travel through an optimal path which is continuously perfect.
In addition, the control method for the robot to advance is suitable for robots with various chassis, for example, the control method can be suitable for robots with flexible chassis, such as robots with spin in place or three-degree-of-freedom chassis, and the like, and also can be suitable for robots with inflexible chassis, such as ackerman vehicle body chassis or two-wheel differential vehicle body chassis, and the robots can safely bypass obstacles on the premise of normal advance through determined target simulation tracks and do not need to avoid the obstacles in a reversing mode and the like in the advancing process.
Compared with the prior art, the embodiment of the invention selects the position coordinates in the pre-stored global path at a distance in front of the current position of the robot as the target reference points of the currently planned local path. The method comprises the steps that a plurality of simulation tracks are correspondingly generated according to a plurality of groups of acquired sampling linear speeds and sampling angular speeds of the robot, the lengths of the generated simulation tracks are larger than or equal to the distance between the robot and a target reference point, the track lengths are set, so that the simulation tracks which cannot bypass the obstacle can be overlapped with the position of the obstacle to a certain extent, when the target simulation track is determined according to the position relation between each simulation track and the obstacle and the position relation between the simulation track and a pre-stored global path, the simulation track which cannot bypass the obstacle cannot be used as the finally determined target simulation track, and the finally determined target simulation track can be ensured to smoothly bypass the obstacle without adjusting the pose of the robot in the advancing process. After the target simulation track is determined, the advancing linear velocity and the angular velocity of the robot are adjusted to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track, so that the robot can bypass the obstacle according to the determined target simulation track, and the advancing safety of the robot is guaranteed.
A second embodiment of the present invention relates to a control method of robot traveling. In the second embodiment of the invention, a plurality of groups of sampling linear velocities and sampling angular velocities are determined by utilizing the curvature radius, so that a plurality of simulation tracks generated according to the sampling linear velocities and the sampling angular velocities do not have repeated tracks, and the effectiveness of generating the simulation tracks is ensured. The specific process is shown in fig. 4, and includes:
And 402, determining the value range of the curvature radius of the simulation track according to the value range of the sampling linear velocity and the value range of the sampling angular velocity of the robot in the simulation time.
Specifically, the value ranges of the sampling linear velocity and the sampling angular velocity of the robot in the simulation time are determined according to the current linear velocity and the current angular velocity of the robot. The simulation time is the time required for the robot to travel from the current position to the target reference point, for example, if the robot is 3 meters from the target reference point, the current linear velocity of the robot is 1 meter per second, and the simulation time may be set to 3 seconds. A slightly larger simulation time value can be set according to actual requirements, and the simulation time value is not limited. After the simulation time is determined, the maximum linear velocity, the minimum linear velocity, the maximum angular velocity and the minimum angular velocity which can be reached by the robot in the simulation time can be calculated. For example, the maximum and minimum values of the sampling linear velocity can be calculated by the following formulas:
wherein v ismaxIs the maximum value of the sampling linear velocity; v. ofminIs the minimum value of the sampling linear velocity; v. of0Is the current traveling linear velocity; vaccmax is the maximum linear acceleration of the robot; t is simulation time;
is the maximum value of the preset linear velocity;
is the maximum value of the preset linear velocity.
Similarly, the maximum and minimum values of the sampling angular velocity can be calculated by the following formula:
wmaxis the maximum value of the sampling angular velocity; w is aminIs the minimum value of the sampling angular velocity; w is a0Is the current angular velocity of travel; aaaccmaxIs the maximum angular acceleration of the robot; t is simulation time;
is the maximum value of the preset angular velocity;
is the maximum value of the preset angular velocity.
After the value range of the sampling linear velocity and the value range of the sampling angular velocity in the simulation time are obtained by calculation, the maximum value of the curvature radius can be calculated according to the minimum value of the sampling linear velocity and the maximum value of the sampling angular velocity, and the maximum value of the curvature radius can be calculated according to the maximum value of the sampling linear velocity and the minimum value of the sampling angular velocity in the same way, as shown in the following formula,
wherein, kappamaxIs the maximum value of the radius of curvature; kappa typeminIs the minimum value of the radius of curvature;
is the maximum value of the preset curvature radius.
And step 403, acquiring curvature radii of a plurality of different values as sampling curvature radii according to the value range of the curvature radii. Specifically, canRandomly acquiring curvature radii of different values in the determined value range of the curvature radii through random sampling to serve as sampling curvature radii; the curvature radius of different values can be orderly determined as the sampling curvature radius through a certain rule. For example, the formula kappa may be utilized by setting the step value dkappan＝min(kappamin+dkappa*n，kappamax) Sampling is carried out, and the value of the curvature radius of the sampling is shown in kappanA numerical value kappa indicating the minimum radius of curvature from the calculationminThe sampling is started until the calculated maximum value of the radius of curvature kappamaxThe number of the collected curvature radius values is n, so that the collected curvature radius data has a certain rule, and the simulation track generated according to the curvature radius is an ordered track, thereby facilitating the subsequent debugging of the generation algorithm of the simulation track.
And step 404, respectively calculating to obtain a plurality of corresponding groups of sampling linear velocities and sampling angular velocities according to the plurality of sampling curvature radii.
And calculating the sampling linear speed corresponding to each sampling curvature radius by utilizing a speed drop function through the preset maximum value and minimum value of the linear speed, the preset maximum value of the curvature radius, the maximum value of the sampling linear speed and each sampling curvature radius. The calculation formula of the deceleration function f (x) is as follows:
wherein f (kappa)n) Is a curvature radius of kappanCalculating the curvature radius of the sampling linear velocity of the corresponding simulation track to be kappanAfter sampling linear velocity of corresponding simulation track, multiplying the calculated sampling linear velocity by the numerical value of curvature radius to obtain sampling angular velocity, for example, calculating sampling angular velocity w by using the following formulan＝vn*kappan，wnFor the calculated sampling angular velocity, vnFor the above calculated sampling linear velocity f (kappa)n)，kappanIs the nth sampled radius of curvature.
And step 407, adjusting the linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track.
In the embodiment, a plurality of simulation tracks are generated by utilizing the sampling curvature radius, and the generated simulation tracks do not coincide with each other, so that the generation of overlapped invalid tracks is avoided, and the efficiency of generating the simulation tracks is improved. When the simulation track is generated, the sampling linear velocity and the angular velocity are determined by using the deceleration function, so that the sampling linear velocity can be regularly generated according to the value of the curvature radius, the robot has higher linear track line velocity, and the linear velocity is reduced according to the bending degree during turning, thereby ensuring that the robot can efficiently and safely advance.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
A third embodiment of the present invention relates to a robot traveling control apparatus, as shown in fig. 5, including: a target reference point determining module 51, an obtaining module 52, a generating module 53, a target simulation track determining module 54 and an adjusting module 55; the target reference point determining module 51 is configured to determine a target reference point for indicating a local traveling target of the robot in a pre-stored global path; the obtaining module 52 is configured to obtain multiple sets of sampling linear velocities and sampling angular velocities of the robot; the generating module 53 is configured to generate a plurality of simulation tracks according to the plurality of sets of sampling linear velocities and sampling angular velocities, where the track lengths of the plurality of simulation tracks are the same and greater than or equal to the distance between the robot and the target reference point; the target simulation track determining module 54 is configured to determine a target simulation track from the generated multiple simulation tracks according to a position relationship between each simulation track and the obstacle and a position relationship between each simulation track and the pre-stored global path; the adjusting module 55 is configured to adjust the linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track.
It should be understood that the present embodiment is a system embodiment corresponding to the first embodiment, and the present embodiment can be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment.
It should be noted that, all the modules involved in this embodiment are logic modules, and in practical application, one logic unit may be one physical unit, may also be a part of one physical unit, and may also be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, a unit which is not so closely related to solve the technical problem proposed by the present invention is not introduced in the present embodiment, but this does not indicate that there is no other unit in the present embodiment.
A fourth embodiment of the present invention relates to a control device for robot travel. As shown in fig. 6, the obtaining module 52 in the fourth embodiment of the present invention includes: a curvature radius determination module 521, a sampling curvature radius acquisition module 522, and a calculation module 523.
The curvature radius determination module 521 is configured to determine a value range of a curvature radius of the simulated track according to a value range of a simulated linear velocity and a value range of a simulated angular velocity of the robot in the simulation time; the sampling curvature radius obtaining module 522 is configured to obtain curvature radii of a plurality of different values as sampling curvature radii according to the value range of the curvature radii; the calculating module 523 is configured to calculate, according to the plurality of sampling curvature radii, to obtain a plurality of corresponding sets of sampling linear velocities and sampling angular velocities.
In addition, the calculating module 523 is configured to calculate, by using a speed drop function, sampling linear speeds corresponding to the respective sampling curvature radii through a maximum value and a minimum value of the preset linear speed, a maximum value of the preset curvature radius, and a maximum value of the sampling linear speed; and calculating to obtain the sampling angular velocity corresponding to the sampling curvature radius according to the sampling curvature radius and the calculated corresponding sampling linear velocity.
In addition, the sampling curvature radius obtaining module 522 is configured to sample a value within a value range of the curvature radius by using a preset sampling step value; the radius of curvature of the sampled value is taken as the sampling radius of curvature.
In addition, the target simulation trajectory determination module 54 is configured to generate a scoring function according to the position information of the obstacle and a pre-stored global path; scoring the generated plurality of simulation tracks through the generated scoring function respectively; and taking the simulation track with the highest score as a target simulation track.
Since the second embodiment corresponds to the present embodiment, the present embodiment can be implemented in cooperation with the second embodiment. The related technical details mentioned in the second embodiment are still valid in this embodiment, and the technical effects that can be achieved in the second embodiment can also be achieved in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the second embodiment.
A fifth embodiment of the present invention relates to an electronic device, as shown in fig. 7, including at least one processor 701; and, a memory 702 communicatively coupled to the at least one processor 701; the memory 702 stores instructions executable by the at least one processor 701, and the instructions are executed by the at least one processor 701, so that the at least one processor 701 can execute the robot travel control method.
The memory 702 and the processor 701 are coupled by a bus, which may comprise any number of interconnecting buses and bridges that couple one or more of the various circuits of the processor 701 and the memory 702. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor is transmitted over a wireless medium via an antenna, which further receives the data and transmits the data to the processor 701.
The processor 701 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And the memory 702 may be used for storing data used by the processor 701 in performing operations.
A sixth embodiment of the present invention relates to a computer-readable storage medium storing a computer program. The computer program realizes the above-described method embodiments when executed by a processor.
A seventh embodiment of the present invention is directed to a robot including at least the above-described electronic apparatus. The robot may perform the above-described control method of robot travel by an electronic device.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific embodiments for practicing the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (11)
1. A method for controlling travel of a robot, comprising:
determining a target reference point for indicating a local traveling target of the robot in a pre-stored global path;
generating a plurality of simulation tracks according to the plurality of groups of sampling linear speeds and sampling angular speeds of the robot; the track lengths of the plurality of simulation tracks are greater than or equal to the distance between the robot and the target reference point;
determining a target simulation track in the generated multiple simulation tracks according to the position relationship between each simulation track and an obstacle and the position relationship between each simulation track and a pre-stored global path;
and adjusting the traveling linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track.
2. The method of controlling robot travel according to claim 1, wherein the plurality of sets of sampling linear velocities and sampling angular velocities of the robot are obtained by:
determining the value range of the curvature radius of the simulation track according to the value range of the simulation linear velocity and the value range of the simulation angular velocity of the robot in the simulation time;
acquiring curvature radii of a plurality of different values as sampling curvature radii according to the value range of the curvature radii;
and respectively calculating to obtain multiple groups of corresponding sampling linear velocities and sampling angular velocities according to the plurality of sampling curvature radii.
3. The method of controlling robot movement according to claim 2, wherein the calculating corresponding sets of the sampling linear velocity and the sampling angular velocity from the plurality of sampling curvature radii, respectively, includes:
calculating sampling linear speeds corresponding to the sampling curvature radii by utilizing a speed drop function through a preset maximum value and a preset minimum value of linear speeds, a preset maximum value of curvature radii, the maximum value of the sampling linear speeds and the sampling curvature radii;
and calculating to obtain the sampling angular velocity corresponding to the sampling curvature radius according to the sampling curvature radius and the corresponding sampling linear velocity.
4. The method for controlling the robot to travel according to claim 2, wherein the step of obtaining a plurality of curvature radii with different values as the sampling curvature radius according to the value range of the curvature radii comprises:
sampling the numerical value in the value range of the curvature radius by a preset sampling stepping value;
and taking the curvature radius of the sampled numerical value as a sampling curvature radius.
5. The method for controlling robot traveling according to claim 1, wherein the determining a target simulation trajectory among the generated plurality of simulation trajectories according to a positional relationship between each of the simulation trajectories and an obstacle and a positional relationship between the simulation trajectory and a pre-stored global path includes:
generating a scoring function according to the position information of the barrier and the pre-stored global path;
respectively scoring the generated plurality of simulation tracks through the generated scoring function;
and taking the simulation track with the highest score as the target simulation track.
6. A control method of robot travel according to any of claims 1-5, wherein the chassis of the robot comprises an Ackerman body chassis or a two-wheeled differential body chassis.
7. A control device for robot traveling, comprising: the system comprises a target reference point determining module, an obtaining module, a generating module, a target simulation track determining module and an adjusting module;
the target reference point determining module is used for determining a target reference point for indicating a local traveling target of the robot in a pre-stored global path;
the acquisition module is used for acquiring a plurality of groups of sampling linear speeds and sampling angular speeds of the robot;
the generating module is used for correspondingly generating a plurality of simulation tracks according to the plurality of groups of sampling linear velocities and sampling angular velocities, and the track lengths of the simulation tracks are greater than or equal to the distance between the robot and the target reference point;
the target simulation track determining module is used for determining a target simulation track in the generated multiple simulation tracks according to the position relation between each simulation track and an obstacle and the position relation between each simulation track and a pre-stored global path;
the adjusting module is used for adjusting the traveling linear velocity and the angular velocity of the robot according to the sampling linear velocity and the sampling angular velocity corresponding to the target simulation track.
8. The control of robot travel of claim 7, wherein the acquisition module comprises: the curvature radius determining module is used for acquiring a sampling curvature radius;
the curvature radius determining module is used for determining the value range of the curvature radius of the simulation track according to the value range of the simulation linear velocity and the value range of the simulation angular velocity of the robot in the simulation time;
the sampling curvature radius acquisition module is used for acquiring curvature radii of a plurality of different values as sampling curvature radii according to the value range of the curvature radii;
and the calculation module is used for respectively calculating and obtaining a plurality of groups of corresponding sampling linear velocities and sampling angular velocities according to the plurality of sampling curvature radii.
9. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of controlling travel of a robot as claimed in any one of claims 1 to 6.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method of controlling travel of a robot according to any one of claims 1 to 6.
11. A robot characterized by comprising at least an electronic device according to claim 9.
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