CN116442245A - Control method, device and system of service robot and storage medium - Google Patents
Control method, device and system of service robot and storage medium Download PDFInfo
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
- B25J9/1666—Avoiding collision or forbidden zones
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The application relates to a control method, a device, a system and a storage medium of a service robot, wherein the method comprises the following steps: acquiring operation intention data from interaction information input by a user, wherein the operation intention data comprises target information and borrowing and returning intention corresponding to a target book; in the constructed virtual map, determining the borrowing and returning point position corresponding to the target book according to the target information; determining current pose information of the service robot in the virtual map, acquiring a first environment parameter acquired when cruising based on a first planned path planned currently, and planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameter and the current pose information to acquire a target corrected path; and controlling the service robot to run to the borrowing and returning point position based on the target correction path, and executing the borrowing and returning operation on the target book. Through the method and the device, the problem that the obstacle avoidance effect is poor and the amplitude of the offset pre-planned path is large when the service robot cruises is solved.
Description
Technical Field
The application relates to the technical field of artificial intelligence, in particular to a control method, a device, a system and a storage medium of a service robot.
Background
The library robot can realize the optimal management of the library, help readers to take books by themselves, finish the carrying and storing work of a large number of books, shorten the time of manual storing and taking out and arranging books, and effectively replace the manual management mode of the library.
In the related art, the laser radar is widely applied to indoor navigation with accurate measurement precision. According to different application scenes, the laser radars with different measurement ranges and different laser beams can be selected, and in an indoor environment, the application requirements can be met by the two-dimensional laser. By utilizing SLAM (Simultaneous Localization And Mapping), i.e., the instant positioning and mapping technique, a library robot can be provided with a map that satisfies the navigation task or even navigate in real-time directly using the technique.
In the related art, a library intelligent service robot performs navigation according to a provided map which is globally consistent, so as to drive the service robot to perform cruising, and provide services such as searching books, returning books and the like for users. However, in the related art, because the matching accuracy of the constructed map and the actual scene is not high, the service robot has poor obstacle avoidance effect when cruising on the path planned and predicted based on the corresponding map, and meanwhile, after gesture adjustment is performed for obstacle avoidance, the deviation amplitude of the corresponding driving path relative to the pre-planned path is large, so that the efficiency and accuracy of the service robot in processing book borrowing and returning tasks are reduced.
Aiming at the problems that the obstacle avoidance effect is poor and the amplitude of deviation from a pre-planned path is large when a service robot cruises based on the planned path in the related art, no effective solution is proposed yet.
Disclosure of Invention
The embodiment of the application provides a control method, a device, a system and a storage medium of a service robot, which at least solve the problems that the service robot has poor obstacle avoidance effect when cruising based on a planned path and has larger amplitude of shifting a pre-planned path during cruising and driving in the related art.
In a first aspect, an embodiment of the present application provides a method for controlling a service robot, including: acquiring operation intention data from interaction information input by a user, wherein the operation intention data comprises target information and borrowing and returning intention corresponding to a target book; determining the borrowing and returning point position corresponding to the target book according to the target information in a constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to a library, and the virtual map is used for representing a real scene corresponding to the library; determining current pose information of the service robot in the virtual map, acquiring first environment parameters acquired when cruising based on a first planned path planned currently, and planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameters and the current pose information to obtain a target corrected path, wherein the first planned path is generated by planning the path based on the borrowing and returning point position and initial pose information corresponding to the service robot; and controlling the service robot to run to the borrowing and returning point position based on the target correction path, and executing the borrowing and returning operation corresponding to the borrowing and returning intention on the target book.
In a second aspect, an embodiment of the present application provides a control device for a service robot, including:
the acquisition module is used for acquiring operation intention data from the interaction information input by the user, wherein the operation intention data comprises target information corresponding to the target book and borrowing and returning intention;
the positioning module is used for determining the borrowing and returning point position corresponding to the target book according to the target information in a constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to a library, and the virtual map is used for representing a real scene corresponding to the library;
the planning module is used for determining current pose information of the service robot in the virtual map, acquiring a first environment parameter acquired when cruising based on a first planned path which is planned currently, planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameter and the current pose information to obtain a target corrected path, wherein the first planned path is generated by planning the path based on the borrowing and returning point position and initial pose information corresponding to the service robot;
And the processing module is used for controlling the service robot to run to the borrowing and returning point position based on the target correction path and executing the borrowing and returning operation corresponding to the borrowing and returning intention on the target book.
In a third aspect, an embodiment of the present application provides a control system for a service robot, including an interaction module, a laser radar module, a transmission module, and a control module; the interaction module and the laser radar module are connected with the control module through the transmission module; the interaction module is used for receiving interaction information input by a user; the laser radar module is used for collecting environment scanning information corresponding to the library; the transmission module is used for transmitting the interaction information and the environment scanning information to the control module; the control module is used for executing the control method of the service robot in the first aspect.
In a fourth aspect, an embodiment of the present application provides a storage medium having stored thereon a computer program which, when executed by a processor, implements a method of controlling a service robot as described in the first aspect above.
Compared with the related art, the control method, the device, the system and the storage medium of the service robot provided by the embodiment of the application acquire operation intention data from the interaction information input by the user, wherein the operation intention data comprises target information corresponding to the target book and borrowing and returning intention; determining the borrowing and returning point position corresponding to the target book according to the target information in a constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to a library, and the virtual map is used for representing a real scene corresponding to the library; determining current pose information of the service robot in the virtual map, acquiring first environment parameters acquired when cruising based on a first planned path planned currently, planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameters and the current pose information to obtain a target corrected path, wherein the first planned path is generated by carrying out path planning based on the borrowed and returned point position and initial pose information corresponding to the service robot; based on the target correction path, the service robot is controlled to run to the borrowing and returning point position, and borrowing and returning operation corresponding to the borrowing and returning intention is performed on the target book, corresponding environment parameters are obtained in real time during cruising, and a preset planning path is corrected according to current pose information and environment parameters of the service robot in a constructed map to obtain an optimal path, so that the service robot can quickly adjust the pose to return to an initially planned path while avoiding the obstacle, the efficiency of the service robot in processing the borrowing and returning book task is improved, the problems that the obstacle avoidance effect is poor and the amplitude of an offset pre-planning path is large during cruising and driving is large during cruising are solved, and the beneficial effects of accurate obstacle avoidance and quick cruising are realized.
The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the other features, objects, and advantages of the application.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 is a hardware configuration block diagram of a terminal of a control method of a service robot of an embodiment of the present application;
FIG. 2 is a flow chart of a method of controlling a service robot according to an embodiment of the present application;
fig. 3 is a block diagram of a control device of a service robot according to an embodiment of the present application.
Description of the embodiments
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described and illustrated below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden on the person of ordinary skill in the art based on the embodiments provided herein, are intended to be within the scope of the present application. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the embodiments described herein can be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar terms herein do not denote a limitation of quantity, but rather denote the singular or plural. The terms "comprising," "including," "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The term "multi-link" as used herein refers to a link greater than or equal to two links. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., "a and/or B" may mean: a exists alone, A and B exist together, and B exists alone. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.
Prior to describing and setting forth specific embodiments of the present application, the related art to which the present application relates will be described herein as follows:
karto SLAM mapping algorithm.
Karto is a 2D laser SLAM solution, which is a sparse graph optimization-based method with closed loop detection. The map optimization method uses the mean value of the map to represent a map, each node represents a position point of the robot track and a sensor measurement data set, and each new node is added and then is calculated and updated. karto takes spa (karto_slam) or g2o (nav 2 d) optimized libraries, and front-end and back-end take single-threaded runs. The Karto algorithm flow mainly comprises three parts of sequence matching, loop detection and back-end optimization. The conditions of the laser key frame in Karto algorithm are as follows: the moving distance of the mobile robot reaches a threshold value, the deflection angle difference value of the mobile robot reaches a threshold value, and the time between the mobile robot and the last key frame reaches a threshold value. After the key frames are obtained, the current key frames and the sub-map are matched by adopting a real-time correlation scanning matching algorithm, the real-time performance of the algorithm is improved by adopting a rough-fine resolution map and a two-dimensional lookup table construction mode, and the pose of the node is obtained. When the mobile robot passes through the vicinity of the once-walking environment, loop detection is carried out, if loop detection conditions are met, the mobile robot enters a rear-end optimization module, the pose of the node is optimized by using a sparse pose adjustment algorithm, accumulated errors are eliminated, and the graph construction precision is improved; if the condition of loop detection is not satisfied, the laser key frame data is continuously received, the sequence matching is carried out, and the steps are repeated.
The algorithm A, also called as the star A algorithm, is a search algorithm applied to static global path planning; the key of the algorithm a is that the evaluation function is selected, specifically, starting from an initial point, searching nodes adjacent to the initial point according to a heuristic function, selecting an optimal adjacent node as a current node through a cost function, continuing to search until a target point is searched, and finally backtracking the target point to the initial point to form a global planning path. The cost estimation function is as follows:
f(x，y) = g (x，y) + h(x，y)
wherein f (x, y) is the valuation function from the starting point to the target point; g (x, y) is the actual cost value from the starting point to the current node; h (x, y) is a heuristic function representing an estimated value of the cost of the current node to the target point. If h (x, y) =0, i.e. the heuristic is zero, the valuation function is determined entirely by g (x, y); if g (x, y) =0, the valuation function is determined entirely by the heuristic function h (x, y).
Dynamic window (Dynamic Window Approach, DWA) algorithm
The DWA algorithm is an algorithm for robot navigation and motion planning. It selects the optimal action from all possible actions by calculating the current state and environmental information of the robot to achieve the predetermined goal. Specifically, the DWA algorithm includes the steps of: acquiring the current state and environmental information of the robot, such as position, speed, obstacles and the like, through a sensor; calculating all possible actions that the robot can take, including different speed and angular speed combinations; predicting the state that each action can reach within a prescribed time by using a kinematic model (such as the kinematic analysis of Mecanum wheels) and limiting the state to be within a dynamic window; for each action within the dynamic window, calculate a score that they can approach the target; the action with the highest score is selected as the next action of the robot.
ROS is a shorthand for Robot Operating System, a robotic operating system.
The method embodiment provided in this embodiment may be executed in a terminal, a computer or a similar computing device. Taking the operation on the terminal as an example, fig. 1 is a block diagram of the hardware structure of the terminal of the control method of the service robot according to the embodiment of the present application. As shown in fig. 1, the terminal may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the structure shown in fig. 1 is merely illustrative and not limiting on the structure of the terminal described above. For example, the terminal may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to a control method of a service robot in an embodiment of the present invention, and the processor 102 executes the computer program stored in the memory 104 to perform various functional applications and data processing, that is, to implement the above-described method. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used to receive or transmit data via a network. The specific examples of the network described above may include a wireless network provided by a communication provider of the terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is configured to communicate with the internet wirelessly.
The present embodiment provides a control method of a service robot running on the terminal, and fig. 2 is a flowchart of a control method of a service robot according to an embodiment of the present application, as shown in fig. 2, where the flowchart includes the following steps:
step S201, operation intention data is obtained from interaction information input by a user, wherein the operation intention data comprises target information corresponding to a target book and borrowing and returning intention.
In the present embodiment, the service robot includes, but is not limited to, an ROS robot, and the interactive information input by the user is to input corresponding operation intention data, that is, to input book target information (for example, a book name, a number) and a borrowing intention (for example, borrowing a book, returning a book) to be borrowed in a dialog box of a UI interface of an operating system of the corresponding service robot by the user; in this embodiment, after the user inputs the corresponding interaction information, the control system corresponding to the service robot determines the related information of the book according to the book name corresponding to the target information in the interaction information, for example: the floor where books are located, book collection room where books are located, bookshelf numbers where books are located, book coordinates corresponding to book returning by means of books, and the determined related information is used as a target for follow-up path planning and guiding the service robot to cruise, for example: and taking the book coordinates as position information of a destination, and further carrying out path planning and serving the end point of the cruising operation of the robot.
Step S202, determining the borrowing and returning point position corresponding to the target book according to the target information in the constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to the library, and the virtual map is used for representing the real scene corresponding to the library.
In this embodiment, before executing the control method of the embodiment of the present application, the virtual map is constructed first; in the embodiment, navigation-free cruising is performed in a library indoor area in advance by a service robot, environment data (such as point cloud data) in the library indoor is scanned in cruising, and then characteristic points in the environment data acquired in the previous time are used as references to be matched with the environment data acquired at present to construct a corresponding virtual map; in this embodiment, the virtual map corresponds to a 2D virtual map; after the virtual map is constructed, the virtual map is stored and used for positioning the initial pose and the current pose of the subsequent service robot, and planning and correcting the related cruising path.
In this embodiment, when the service robot is started to perform the book borrowing and returning operation, the destination of the service robot cruising and the end position of the path planning, that is, the corresponding borrowing and returning point position, are determined according to the target to be operated, that is, the target information corresponding to the target book, for example: and a coordinate point of book coordinates corresponding to the target book in the virtual map.
Step S203, determining current pose information of the service robot in the virtual map, acquiring a first environment parameter acquired when cruising based on a first planned path which is planned currently, and planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameter and the current pose information to obtain a target corrected path, wherein the first planned path is generated by carrying out path planning based on return points and initial pose information corresponding to the service robot.
In this embodiment, the current pose information and the initial pose information both include the corresponding position and direction; the first planning path is planned when the service robot starts cruising, and is generated by carrying out global path planning according to initial pose information and borrowing and returning points of the service robot in the virtual map at an initial moment; the first planning path is used for guiding the service robot to cruise, and when the service robot needs to avoid the obstacle, the correction of the local path is started so as to realize the obstacle avoidance through the optimal local path of the local correction, and the service robot returns to the first planning path after the obstacle avoidance is completed.
In this embodiment, during the cruising process of the service robot according to the first planned path that has been planned at present, determining current pose information, path state and obtaining the first environmental parameter in real time, and meanwhile, determining whether to correct the current path by determining the path state and determining the obstacle information in the first environmental parameter; when the path correction is judged to be needed, local path planning correction is carried out according to the current pose information and the first environment parameter, and then a corrected target path is obtained.
It should be noted that, before the current moment, the service robot also needs to avoid the obstacle to perform the path correction, but what is considered in the embodiments of the present application is the cruising path at the current moment and after the current moment, it can be understood that it is also necessarily understood that, before the current moment, whether the service robot performs the obstacle avoidance or the path correction, at the current moment, the service robot has cruises to the position corresponding to the current moment, and the position is a certain node on the first planned path, so that the cruising performed before the current moment does not affect the planning of the obstacle avoidance cruising and the path correction after the current moment.
Step S204, based on the target correction path, the service robot is controlled to run to the borrowing and returning point position, and the borrowing and returning operation corresponding to the borrowing and returning intention is executed on the target book.
In this embodiment, after the path planning correction is performed, the service robot cruises according to the local path (a small path from the current position to the borrowing and returning point position, and a small path for realizing obstacle avoidance) corrected by the planning, and finally, cruises to the borrowing and returning point position are implemented to perform the borrowing and returning operation on the target book.
Through the steps S201 to S204, operation intention data is obtained from the interaction information input by the user, wherein the operation intention data includes target information and borrowing and returning intention corresponding to the target book; in the constructed virtual map, determining the borrowing and returning point position corresponding to the target book according to the target information, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to the library, and the virtual map is used for representing a real scene corresponding to the library; determining current pose information of the service robot in the virtual map, acquiring first environment parameters acquired when cruising based on a first planned path which is planned currently, planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameters and the current pose information to obtain a target corrected path, wherein the first planned path is generated by planning a path based on the borrowed point position and initial pose information corresponding to the service robot; based on the target correction path, the service robot is controlled to run to a borrowing and returning point position, borrowing and returning operation corresponding to borrowing and returning intention is performed on the target book, corresponding environment parameters are obtained in real time during cruising, and a preset planning path is corrected according to current pose information and the environment parameters of the service robot in a constructed map to obtain an optimal path, so that the service robot can quickly adjust the pose to return to an initially planned path while avoiding the obstacle, the efficiency of the service robot in processing the borrowing and returning book task is improved, the problems that the obstacle avoidance effect is poor and the amplitude of shifting the pre-planned path is large during cruising and driving based on the planned path in the prior art are solved, and the beneficial effects of accurate obstacle avoidance and quick cruising are realized.
It should be noted that, in the embodiment of the present application, the service robot realizes the perception of the real environment based on the preset navigation function packet, completes the construction of the virtual map (2D) of the real scene, correspondingly performs self-positioning on the virtual map based on the position of the service robot in the real environment, performs path planning based on the borrowing and returning point position, obtains the optimal path, realizes the navigation and obstacle avoidance based on the data detected in real time, and finally reaches the borrowing and returning point position.
In some embodiments, according to the first environmental parameter and the current pose information, the first planned path is corrected by using a preset path planning algorithm to obtain a target corrected path, including the following steps:
and 21, detecting the position information of the obstacle in the first environment parameter, and determining a first position node where the service robot is currently located according to the current pose information.
In this embodiment, the first environmental parameter includes at least scanned position information of the obstacle in the virtual map (e.g., position coordinates of the obstacle corresponding to the obstacle in the virtual map); detecting a first environmental parameter to determine whether an obstacle exists in front of a current cruising path of the service robot, whether obstacle avoidance is needed or not, and carrying out local path correction for obstacle avoidance; when it is determined that obstacle avoidance and local path correction are required, an optimal path capable of carrying out obstacle avoidance needs to be planned according to the current position node, so that when path correction planning is carried out, obstacle information and the current first position node need to be acquired.
Step 22, according to the first position node, a first local path is obtained from the first planned path, wherein the first local path is used for representing a path for the service robot to travel from the first position node to the borrowing and returning point in a preset time period, and the end point of the first local path is one position node of the first planned path.
In this embodiment, whether obstacle avoidance is needed is determined, and if an obstacle exists in the environmental parameters around the server robot, whether the obstacle is on a path (i.e., a first local path) of the first planned path after the first position node where the first planned path is located currently is determined; in this embodiment, the first local path may be a local path with a preset path length, or may be a path with a preset number of location nodes.
Step 23, detecting obstacle nodes corresponding to the obstacle position information in all pose nodes corresponding to the first local path.
In this embodiment, after determining a first local path from the first position node where the current position node is located, obstacle position information is detected in the first local path, that is, it is determined whether or not the obstacle node corresponding to the obstacle position information is one of all the pose nodes corresponding to the first local path.
In this embodiment, when the obstacle avoidance is required, the selected first local path is necessarily the obstacle node corresponding to the obstacle of the path, and at this time, the end point of the first local path is necessarily a node located after the obstacle node on the first planned path.
And step 24, under the condition that the obstacle node is detected, generating a second local path based on the first position node, the end point of the first local path and a preset path planning algorithm, and correcting the first planned path based on the second local path to obtain a target corrected path.
In this embodiment, when it is determined that the obstacle node corresponding to the obstacle position information is one of all pose nodes corresponding to the first local path, it indicates that obstacle avoidance is required, and at the same time, an optimal local planning path capable of avoiding the obstacle and quickly returning to the first planning path needs to be planned by repair, and when correction planning is performed, local path correction planning needs to be performed with reference to the first position node where the current position information is located and the end point of the first local path, so as to obtain an optimal local path capable of implementing obstacle avoidance, that is, a second local path; in this embodiment, when the local path correction planning is performed with reference to the first position node and the end point of the first local path, the distance between the service robot and the obstacle node is also referred to, so that when the second local path is planned, the service robot cruises according to the second local path to avoid the obstacle and quickly returns to the first planned path.
It will be appreciated that in some embodiments, when performing the local path correction planning, the second local path drawn by the correction rule is a path that retreats from the first position node to the cruising node and then moves from the cruising node toward the end of the first local path due to the structure of the indoor scene and the limitation of the actual scene.
In some alternative embodiments, the preset path planning algorithm includes a dynamic window DWA path planning algorithm, and the second local path is generated based on the first location node, the end point of the first local path, and the preset path planning algorithm, by: and respectively taking the first position node and the end point of the first local path as a starting node and a terminating node, and carrying out local path planning by using a DWA path planning algorithm to generate a second local path.
It should be understood that when the DWA path planning algorithm is used to perform local path planning, the first position node is used as an initial position point, the DWA path planning algorithm is used to calculate the node reached by the service robot in the next step, and the operations are sequentially repeated until the node reached in the next step is the end point of the first local path. It will be appreciated that the path planning may be performed using a DWA path planning algorithm, and the specific implementation is not limited to this application, but may be any existing path planning method using a DWA algorithm.
Detecting obstacle position information in the first environment parameter in the steps, and determining a first position node where the service robot is currently located according to the current pose information; according to the first position node, a first local path is obtained from the first planning path; detecting obstacle nodes corresponding to the obstacle position information in all pose nodes corresponding to the first local path; under the condition that an obstacle node is detected, generating a second local path based on the first position node, the end point of the first local path and a preset path planning algorithm, and correcting the first planned path based on the second local path to obtain a target corrected path; through planning the second local path again based on the current position node, the obstacle node and the end point of the first local path, when the service robot cruises according to the second local path, the service robot accurately carries out obstacle avoidance and quickly returns to the first planning path, thereby realizing quick cruising navigation and obstacle avoidance and improving the efficiency of the service robot in processing the task of borrowing and returning books.
In some embodiments, the correcting the first planned path based on the second local path in step 24 obtains a target corrected path by:
Step 31, selecting a first path to be cruised from the first position node to the borrowing and returning point position from the first planning path, wherein the first path to be cruised comprises a first local path.
And step 32, correcting and replacing the first local path and the second local path in the first path to be cruised to obtain a target corrected path.
In this embodiment, the first position node is preceded by a path on which the service robot has completed cruising, and the path to be cruised, that is, the path from the first position node to the next in the first planned path, needs to be corrected; therefore, the part to be cruised in the first planned path can be corrected by replacing the first partial path with the second partial path which is re-planned and has the obstacle in the first path to be cruised.
Selecting a first path to be cruised from the first position node to the borrowing and returning point position from the first planning path in the steps; and correcting and replacing the first local path and the second local path in the first path to be cruised to obtain a target corrected path, so that when the service robot needs to avoid the obstacle or deviate from a preset path, the local path correction planning is performed, and the quick obstacle avoidance and the quick arrival of the service robot at the borrowing and returning point position are realized through local dynamic adjustment.
In some of these embodiments, determining current pose information of the service robot in the virtual map includes the steps of: and running a virtual map by using preset visual application software Rviz, and in the running virtual map, positioning the service robot by using an adaptive Monte Carlo positioning AMCL instance associated with the navigation function package to obtain current pose information.
In this embodiment, an operating system ROS corresponding to the service robot starts a self-contained visual application software Rviz virtual map, and then, specifies an initial Pose of the service robot using a positioning service (2D post Estimate) provided by an AMCL node in a preset navigation function package (corresponding to a navigation function package in the ROS operating system); and then, the navigation function package uses the AMCL node to perform self-positioning on the service robot by a Monte Carlo positioning method, and estimates the current pose information of the robot.
In some embodiments, path planning is performed based on initial pose information corresponding to the borrowed and returning point position and the service robot, and a first planned path is generated, which is realized through the following steps:
and step 41, positioning the initial position of the service robot by utilizing the self-adaptive Monte Carlo positioning AMCL instance associated with the navigation function package to obtain initial pose information.
And 42, carrying out global path planning by adopting a heuristic A star searching algorithm based on the initial pose information and borrowing and returning point position information to generate a first planning path.
In this embodiment, after the service robot completes self-positioning, that is, positioning and obtaining initial pose information, a path planning service (for example, 2D Nav gold) provided by a navigation function package is used to specify a target position of the service robot, that is, a return point position, and then the navigation function package uses a global path planning algorithm (for example, heuristic a star search algorithm a) to generate a global path for the service robot to cruise from the initial pose to the target position, that is, to generate a first planned path.
The initial position of the service robot is positioned through the self-adaptive Monte Carlo positioning AMCL instance related by the navigation function package, so that initial pose information is obtained; based on the initial pose information and borrowing and returning points, a heuristic A star search algorithm is adopted to conduct global path planning, a first planning path is generated, and initial planning of the first planning path for cruising and book borrowing and returning service of the service robot in a library is achieved.
In some embodiments, the environment scanning information includes point cloud data, and the virtual map is constructed by using a preset navigation function package and environment scanning information corresponding to the library, including the following steps:
step 51, acquiring multi-frame point cloud data, wherein the point cloud data is sensed by a laser radar when the service robot cruises in a library indoor area.
And 52, processing multi-frame point cloud data by using a synchronous positioning and composition Karto SLAM algorithm based on graph optimization to generate a virtual map.
In the embodiment, navigation-free cruising is performed in the library indoor area in advance by the service robot, and environment data in the library is scanned in cruising to obtain multi-frame point cloud data. In some of the preferred embodiments of the present invention,
the specific mapping steps comprise:
step 1, task initialization is performed on a Slam library of the ROS operating system corresponding to the service robot, namely, an empty 2D map is created, the pose (including the position and the direction) of the service robot is initialized, and parameters (such as map resolution and sensor parameters) of a Karto SLAM algorithm are set.
And 2, moving the service robot, measuring the distance and angle information of the surrounding environment by using a laser radar, fusing the sensor data with the pose information of the service robot, and recording to obtain corresponding point cloud data.
And 3, matching the current scanning data (corresponding to the current point cloud data) with the known point cloud data by using the characteristic points of the known point cloud data (the acquired point cloud data) as references, and calculating the matched pose transformation by using a three-dimensional point cloud matching (Iterative Closest Point, abbreviated as ICP) algorithm.
And 4, optimizing the consistency of the map and the accuracy of the robot pose by using a graph-based optimization algorithm, and adjusting the feature points in the map and the service robot pose to reduce the matching error to the greatest extent.
And 5, updating map data, fusing newly scanned point cloud data with existing data, updating map feature points and tracks of the service robot, and updating the pose of the service robot.
And 6, repeating the steps 2 to 5 until the map is perfect, and storing the map data into a fixed format to finish the map building.
Through the steps, multi-frame point cloud data are obtained, the multi-frame point cloud data are processed by using a synchronous positioning and composition Karto SLAM algorithm based on graph optimization, a virtual map is generated, the map construction of a library indoor scene is realized, and data are provided for navigation and obstacle avoidance of a service robot.
The following describes a control method of the service robot according to the preferred embodiment of the present application as follows:
the service robot of the embodiment of the application uses an A and DWA path planning algorithm, a Karto mapping algorithm and an open source navigation function package in an ROS operation system to realize the perception of the intelligent robot to a real environment, complete the construction of a 2D virtual map of the real scene, correspondingly self-locate the 2D virtual map based on the position of the robot in the real environment, and receive a target point coordinate for path planning, so as to obtain an optimal path, realize navigation and obstacle avoidance based on data detected by a radar in real time, and finally reach a target position.
The service robot of this application embodiment includes four big modules, specifically includes: the system comprises a control module, a laser radar module, an information retrieval module and a user interaction module, wherein the information retrieval module and the user interaction module can also adopt an integrated interaction module; in this embodiment: the control module comprises a bottom layer driving module and an upper computer module which are respectively responsible for controlling bottom layer hardware of the service robot and executing and communicating upper layer functions; the laser radar module is responsible for detecting a real environment, returning data information to the upper computer, receiving an instruction of the upper computer and executing corresponding functional modules and data transmission; the user interaction module is mainly responsible for receiving the instruction of the client and responding and executing corresponding functional operation; the information retrieval module is mainly responsible for receiving the client instructions and retrieving the databases carried by the information retrieval module, acquiring target information and sending the target information to the upper computer. In particular, the method comprises the steps of,
The bottom driving module is connected with and controls bottom hardware such as a motor, a steering engine and the like, and is communicated with the upper computer through a Micro-USB serial port; the upper computer communication module is mainly responsible for sending control instructions to the bottom driver, deploying and calling laser radar related functions, information retrieval functions and user interaction functions, and the communication of all parts and the control of the upper computer to the bottom driver are realized based on an ROS robot operating system.
In the laser radar module, the functions of autonomous positioning, image construction, navigation, obstacle avoidance and the like of the service robot are realized through the laser radar, the laser radar scans the environment of a library indoor scene, a corresponding 2D virtual map is constructed, autonomous positioning and navigation are carried out according to the corresponding 2D map, whether an obstacle exists on a preset path or not can be judged, coordinates of the obstacle in front and the distance from the laser radar are acquired, and therefore the service robot can judge whether to execute the operation from deceleration to stopping and the deviation condition of an actual path and the preset path after detecting the obstacle, and the service robot can carry out posture adjustment to return to a normal path.
In the information retrieval module, basic information of books in a library is stored mainly through constructing an SQL database, and contents such as book numbers, book names, authors, book storage room numbers, book storage shelf numbers, floor numbers, book states, coordinate information of book shelves and the like are stored. The communication between the intelligent robot and the database is realized by calling the ROS and the API interface of the database through the ROS robot operating system, and the data access function provided by the ROS is used for searching and sending the database information.
In the user interaction module, a UI interface is designed mainly based on a QT module in an ROS robot operating system, a dialog box is arranged in the UI interface, a user can send a book returning instruction to an intelligent robot by inputting a corresponding book name/number, the intelligent robot retrieves a database to obtain coordinate information of a bookshelf where a book is located by processing information input by the user, and a cruising function is started to transport the book to a target position.
The embodiment also provides a control device of the service robot, which is used for implementing the above embodiment and the preferred embodiment, and is not described in detail. As used below, the terms "module," "unit," "sub-unit," and the like may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
Fig. 3 is a block diagram of a control device of a service robot according to an embodiment of the present application, and as shown in fig. 3, the device includes an acquisition module 31, a positioning module 32, a planning module 33, and a processing module 34, wherein,
the acquiring module 31 is configured to acquire operation intention data from interaction information input by a user, where the operation intention data includes target information and borrowing and returning intention corresponding to a target book;
The positioning module 32 is coupled to the obtaining module 31 and is used for determining the borrowing and returning point position corresponding to the target book according to the target information in a constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to the library, and the virtual map is used for representing a real scene corresponding to the library;
the planning module 33 is coupled with the positioning module 32, and is used for determining current pose information of the service robot in the virtual map, acquiring a first environment parameter acquired when cruising based on a first planned path which is planned currently, and planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameter and the current pose information to obtain a target correction path, wherein the first planned path is generated by carrying out path planning based on return points and initial pose information corresponding to the service robot;
the processing module 34 is coupled to the planning module 33, and is configured to control the service robot to operate to the borrowing and returning position based on the target correction path, and perform a borrowing and returning operation corresponding to the borrowing and returning intention on the target book.
According to the control device of the service robot, operation intention data are obtained from interaction information input by a user, wherein the operation intention data comprise target information corresponding to a target book and borrowing and returning intention; in the constructed virtual map, determining the borrowing and returning point position corresponding to the target book according to the target information, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to the library, and the virtual map is used for representing a real scene corresponding to the library; determining current pose information of the service robot in the virtual map, acquiring first environment parameters acquired when cruising based on a first planned path which is planned currently, planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameters and the current pose information to obtain a target corrected path, wherein the first planned path is generated by planning a path based on the borrowed point position and initial pose information corresponding to the service robot; based on the target correction path, the service robot is controlled to run to a borrowing and returning point position, borrowing and returning operation corresponding to borrowing and returning intention is performed on the target book, corresponding environment parameters are obtained in real time during cruising, and a preset planning path is corrected according to current pose information and the environment parameters of the service robot in a constructed map to obtain an optimal path, so that the service robot can quickly adjust the pose to return to an initially planned path while avoiding the obstacle, the efficiency of the service robot in processing the borrowing and returning book task is improved, the problems that the obstacle avoidance effect is poor and the amplitude of shifting the pre-planned path is large during cruising and driving based on the planned path in the prior art are solved, and the beneficial effects of accurate obstacle avoidance and quick cruising are realized.
In some of these embodiments, the planning module 33 further includes:
the first detection unit is used for detecting the position information of the obstacle in the first environment parameter and determining a first position node where the service robot is currently located according to the current pose information.
The first acquisition unit is coupled with the first detection unit and is used for acquiring a first local path from the first planning path according to the first position node, wherein the first local path is used for representing a path of the service robot traveling from the first position node to the borrowing and returning point in a preset time period, and the end point of the first local path is one position node of the first planning path.
The second detection unit is coupled with the first acquisition unit and is used for detecting obstacle nodes corresponding to the obstacle position information in all pose nodes corresponding to the first local path.
The first planning unit is coupled with the second detection unit and is used for generating a second local path based on the first position node, the end point of the first local path and a preset path planning algorithm under the condition that the obstacle node is detected, and correcting the first planning path based on the second local path to obtain a target corrected path.
In some embodiments, the first planning unit is further configured to select a first path to be cruised from the first position node to the borrowing and returning point position from the first planned path, where the first path to be cruised includes a first local path; and correcting and replacing the first local path and the second local path in the first path to be cruised to obtain a target corrected path.
In some embodiments, the preset path planning algorithm includes a dynamic window DWA path planning algorithm, and the first planning unit is further configured to use the first location node and the end point of the first local path as a start node and an end node, respectively, and perform local path planning by using the DWA path planning algorithm to generate the second local path.
In some of these embodiments, determining current pose information of the service robot in the virtual map includes: and running the virtual map by using preset visual application software Rviz, and in the running virtual map, positioning the service robot by using an adaptive Monte Carlo positioning AMCL instance associated with the navigation function package to obtain the current pose information.
In some embodiments, the planning module 33 is further configured to perform initial position location on the service robot by using the adaptive monte carlo positioning AMCL instance associated with the navigation function package, to obtain initial pose information; based on the initial pose information and borrowing and returning point positions, a heuristic A star searching algorithm is adopted to conduct global path planning, and a first planning path is generated.
In some embodiments, the environmental scan information comprises point cloud data, the control device of the service robot further configured to obtain multi-frame point cloud data, wherein the point cloud data is sensed by the lidar when the service robot cruises in the library indoor region; and processing multi-frame point cloud data by using a synchronous positioning and composition Karto SLAM algorithm based on graph optimization to generate a virtual map.
The embodiment also provides a control system of the service robot, which comprises: the system comprises an interaction module, a laser radar module, a transmission module and a control module; the interaction module and the laser radar module are connected with the control module through the transmission module; the interaction module is used for receiving interaction information input by a user; the laser radar module is used for collecting environment scanning information corresponding to the library; the transmission module is used for transmitting the interaction information and the environment scanning information to the control module; the control module is configured to perform the steps of any of the method embodiments described above.
The present embodiment also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, acquiring operation intention data from interaction information input by a user, wherein the operation intention data comprises target information and borrowing and returning intention corresponding to a target book.
S2, determining the borrowing and returning point position corresponding to the target book according to the target information in the constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to the library, and the virtual map is used for representing a real scene corresponding to the library.
S3, determining current pose information of the service robot in the virtual map, acquiring first environment parameters acquired when cruising based on a first planned path which is planned currently, planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameters and the current pose information to obtain a target corrected path, wherein the first planned path is generated by carrying out path planning based on return points and initial pose information corresponding to the service robot.
S4, controlling the service robot to run to the borrowing and returning point position based on the target correction path, and executing borrowing and returning operation corresponding to the borrowing and returning intention on the target book.
It should be noted that, specific examples in this embodiment may refer to examples described in the foregoing embodiments and alternative implementations, and this embodiment is not repeated herein.
In addition, in combination with the control method of the service robot in the above embodiment, the embodiment of the application may provide a storage medium for implementation. The storage medium has a computer program stored thereon; the computer program, when executed by a processor, implements the control method of any one of the service robots of the above embodiments.
It should be understood by those skilled in the art that the technical features of the above embodiments may be combined in any manner, and for brevity, all of the possible combinations of the technical features of the above embodiments are not described, however, they should be considered as being within the scope of the description provided herein, as long as there is no contradiction between the combinations of the technical features.
The foregoing examples represent only a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A control method of a service robot, comprising:
acquiring operation intention data from interaction information input by a user, wherein the operation intention data comprises target information and borrowing and returning intention corresponding to a target book;
determining the borrowing and returning point position corresponding to the target book according to the target information in a constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to a library, and the virtual map is used for representing a real scene corresponding to the library;
determining current pose information of the service robot in the virtual map, acquiring first environment parameters acquired when cruising based on a first planned path planned currently, and planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameters and the current pose information to obtain a target corrected path, wherein the first planned path is generated by planning the path based on the borrowing and returning point position and initial pose information corresponding to the service robot;
and controlling the service robot to run to the borrowing and returning point position based on the target correction path, and executing the borrowing and returning operation corresponding to the borrowing and returning intention on the target book.
2. The method of claim 1, wherein correcting the first planned path using a preset path planning algorithm according to the first environmental parameter and the current pose information to obtain a target corrected path comprises:
detecting obstacle position information in the first environment parameters, and determining a first position node where the service robot is currently located according to the current pose information;
acquiring a first local path from the first planning path according to the first position node, wherein the first local path is used for representing a path of the service robot running from the first position node to the borrowing and returning point in a preset time period, and the end point of the first local path is one position node of the first planning path;
detecting obstacle nodes corresponding to the obstacle position information in all pose nodes corresponding to the first local path;
and under the condition that the obstacle node is detected, generating a second local path based on the first position node, the end point of the first local path and a preset path planning algorithm, and correcting the first planned path based on the second local path to obtain the target corrected path.
3. The method of claim 2, wherein modifying the first planned path based on the second local path to obtain the target modified path comprises:
selecting a first path to be cruised from the first position node to the borrowing and returning point position from the first planning path, wherein the first path to be cruised comprises the first local path;
and correcting and replacing the first local path and the second local path in the first path to be cruised to obtain the target corrected path.
4. The method of claim 2, wherein the pre-set path planning algorithm comprises a dynamic window DWA path planning algorithm, generating a second local path based on the first location node, the end point of the first local path, and a pre-set path planning algorithm, comprising: and respectively taking the first position node and the end point of the first local path as a starting node and a terminating node, and carrying out local path planning by using the DWA path planning algorithm to generate the second local path.
5. The method of claim 1, wherein determining current pose information of the service robot in the virtual map comprises: and running the virtual map by using preset visual application software Rviz, and in the running virtual map, positioning the service robot by using an adaptive Monte Carlo positioning AMCL instance associated with the navigation function package to obtain the current pose information.
6. The method of claim 5, wherein generating the first planned path based on the borrowing and returning point location and initial pose information corresponding to a service robot comprises:
utilizing the self-adaptive Monte Carlo positioning AMCL instance associated with the navigation function package to perform initial position positioning on the service robot to obtain the initial pose information;
and carrying out global path planning by adopting a heuristic A star searching algorithm based on the initial pose information and the borrowing and returning point position, and generating the first planning path.
7. The method of claim 1, wherein the environment scanning information includes point cloud data, and constructing the virtual map using a preset navigation function package and environment scanning information corresponding to the library includes:
acquiring multi-frame point cloud data, wherein the point cloud data is sensed by a laser radar when a service robot cruises in a library indoor area;
and processing the multi-frame point cloud data by using a synchronous positioning and composition Karto SLAM algorithm based on graph optimization to generate the virtual map.
8. A control device for a service robot, comprising:
The acquisition module is used for acquiring operation intention data from the interaction information input by the user, wherein the operation intention data comprises target information corresponding to the target book and borrowing and returning intention;
the positioning module is used for determining the borrowing and returning point position corresponding to the target book according to the target information in a constructed virtual map, wherein the virtual map is constructed according to a preset navigation function package and environment scanning information corresponding to a library, and the virtual map is used for representing a real scene corresponding to the library;
the planning module is used for determining current pose information of the service robot in the virtual map, acquiring a first environment parameter acquired when cruising based on a first planned path which is planned currently, planning and correcting the first planned path by using a preset path planning algorithm according to the first environment parameter and the current pose information to obtain a target corrected path, wherein the first planned path is generated by planning the path based on the borrowing and returning point position and initial pose information corresponding to the service robot;
and the processing module is used for controlling the service robot to run to the borrowing and returning point position based on the target correction path and executing the borrowing and returning operation corresponding to the borrowing and returning intention on the target book.
9. A control system for a service robot, comprising: the system comprises an interaction module, a laser radar module, a transmission module and a control module; the interaction module and the laser radar module are connected with the control module through the transmission module;
the interaction module is used for receiving interaction information input by a user;
the laser radar module is used for collecting environment scanning information corresponding to the library;
the transmission module is used for transmitting the interaction information and the environment scanning information to the control module;
the control module is configured to execute the control method of the service robot according to any one of claims 1 to 7.
10. A storage medium having stored thereon a computer program, which when executed by a processor, implements the method of controlling a service robot according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116901090A (en) * | 2023-09-14 | 2023-10-20 | 浩科机器人（苏州）有限公司 | Control method of multi-axis degree-of-freedom robot |
| CN117076591A (en) * | 2023-10-17 | 2023-11-17 | 大扬智能科技(北京)有限公司 | Map generation method and device for robot, robot and readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116901090A (en) * | 2023-09-14 | 2023-10-20 | 浩科机器人（苏州）有限公司 | Control method of multi-axis degree-of-freedom robot |
| CN116901090B (en) * | 2023-09-14 | 2023-11-28 | 浩科机器人（苏州）有限公司 | Control method of multi-axis degree-of-freedom robot |
| CN117076591A (en) * | 2023-10-17 | 2023-11-17 | 大扬智能科技(北京)有限公司 | Map generation method and device for robot, robot and readable storage medium |
| CN117076591B (en) * | 2023-10-17 | 2024-02-23 | 大扬智能科技(北京)有限公司 | Map generation method and device for robot, robot and readable storage medium |
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