CN113524193B - Robot motion space marking method and device, robot and storage medium - Google Patents
Robot motion space marking method and device, robot and storage medium Download PDFInfo
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- CN113524193B CN113524193B CN202110895691.6A CN202110895691A CN113524193B CN 113524193 B CN113524193 B CN 113524193B CN 202110895691 A CN202110895691 A CN 202110895691A CN 113524193 B CN113524193 B CN 113524193B
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Abstract
The invention provides a robot motion space marking method, which comprises the following steps: acquiring a detection data frame of a robot in a motion space, and establishing a 3D point cloud map and a 2D map in the motion space according to the detection data frame; acquiring a first point cloud map below a plane where the robot height is located by using the 3D point cloud map and the robot height; determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the robot working data; sampling the motion route, and calculating a contour point cloud of the robot on the motion route by combining robot contour data; and acquiring risk points of robot motion according to the first point cloud map and the contour point cloud, and marking the risk points, thereby solving the problem that the robot motion route planning excessively depends on the experience of engineering personnel.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a robot motion space marking method, a device, a robot and a storage medium.
Background
Before the robot capable of moving autonomously enters an application site, the most important thing is to set a motion route of the robot. However, most of the existing routes are established manually according to the field conditions by construction personnel on the engineering site, and whether the established movement route is proper or not depends on the experience and the capability of the field construction personnel completely, but because the field environment is complicated and changeable and unpredictable environmental obstacles often appear, the movement route of the robot which is preset can generate great obstacles for the anti-interference capability of the movement of the robot, so that a real-time marking method for the movement route of the autonomous mobile robot is urgently needed to be provided, the movement route of the robot is reasonably planned, and the robot can autonomously move in various environments without being blocked by the environmental obstacles too much.
Disclosure of Invention
The invention aims to provide a robot motion space marking method, a robot motion space marking device, a robot and a computer storage medium, which are used for solving the problem that the robot motion route planning excessively depends on the experience of engineering personnel.
The technical scheme provided by the invention is as follows:
a robot motion space labeling method, comprising:
acquiring a detection data frame of a robot in a motion space, and establishing a 3D point cloud map and a 2D map in the motion space according to the detection data frame;
acquiring a first point cloud map below a plane where the robot height is located by using the 3D point cloud map and the robot height;
determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the robot working data;
sampling the motion route, and calculating a contour point cloud of the robot on the motion route by combining robot contour data;
and acquiring risk points of robot motion according to the first point cloud map and the contour point cloud, and marking the risk points.
Preferably, the acquiring the risk points of the robot motion according to the first point cloud map and the contour point cloud, and marking the risk points specifically includes:
acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map;
acquiring a second risk point set of robot movement according to the movement route and the first point cloud map;
marking the first set of risk points and the second set of risk points in a robot motion space.
Preferably, the step of acquiring the first risk point set of the robot motion according to the contour point cloud and the first point cloud map specifically comprises:
traversing each point in the contour point cloud, and obtaining the distance from each point in the contour point cloud to a KD tree constructed according to the first point cloud map;
acquiring a first closest distance from the outline point cloud to the KD tree and a point corresponding to the first closest distance;
when the first closest distance is smaller than a preset first distance threshold, taking a point corresponding to the first closest distance on the contour point cloud as a first risk point;
saving the first risk point in the first risk point set.
Preferably, the acquiring a second risk point set of robot motion according to the motion route and the first point cloud map specifically includes:
acquiring an area of interest within a preset distance range of the movement route where the robot walks on the 2D map;
traversing each point in the region of interest, and obtaining the distance between each point in the region of interest and a KD tree constructed according to the first point cloud map;
acquiring a second closest distance from the KD tree in the region of interest and a point corresponding to the second closest distance;
when the second closest distance is smaller than a preset second distance threshold, taking a point corresponding to the second closest distance on the region of interest as a second risk point;
and saving the second risk point in the second risk point set.
In order to achieve the object of the present invention, an embodiment of the present invention further provides a robot motion space marking apparatus, where the apparatus includes:
the map building module is used for building a 3D point cloud map and a 2D map under the motion environment by collecting detection data frames of the robot under the motion environment and according to the detection data frames;
the first point cloud map calculation module is used for acquiring a first point cloud map below a plane where the robot height is located by using the 3D point cloud map and the robot height;
the movement route determining module is used for determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the robot working data;
the contour point cloud computing module is used for sampling the motion route and computing the contour point cloud of the robot on the motion route by combining robot contour data;
and the motion space marking module is used for acquiring risk points of robot motion according to the first point cloud map and the contour point cloud and marking the risk points.
Preferably, the motion space labeling module specifically includes:
the first computing unit is used for acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map;
the second computing unit is used for acquiring a second risk point set of robot motion according to the motion route and the first point cloud map;
a marking unit for marking the first set of risk points and the second set of risk points in a robot motion space.
Preferably, the first calculation unit includes:
a subunit, configured to traverse each point in the contour point cloud, and obtain a distance from each point in the contour point cloud to a KD tree constructed according to the first point cloud map;
a subunit, configured to obtain a first closest distance from the KD tree in the contour point cloud and a point corresponding to the first closest distance;
a subunit, configured to, when the first closest distance is smaller than a preset first distance threshold, take a point corresponding to the first closest distance on the contour point cloud as a first risk point;
a subunit for saving the first risk point in the first set of risk points.
Preferably, the second calculation unit includes:
a sub-unit for obtaining a region of interest within a preset distance range of the movement route traveled by the robot on the 2D map;
a subunit configured to traverse each point in the region of interest, and obtain a distance from each point in the region of interest to a KD tree constructed according to the first point cloud map;
a subunit, configured to obtain a second closest distance from the KD tree in the region of interest and a point corresponding to the second closest distance;
a subunit, configured to, when the second closest distance is smaller than a preset second distance threshold, take a point on the region of interest corresponding to the second closest distance as a second risk point;
a subunit for saving the second risk point in the second set of risk points.
To achieve the objective of the present invention, the present invention also provides a robot, which includes a processor and a memory, the processor is coupled with the memory, wherein,
the memory is used for storing programs;
the processor is used for executing the program in the memory, so that the robot can execute any method for realizing the robot motion space marking.
In order to achieve the object of the present invention, the embodiment of the present invention further provides a computer-readable storage medium, which stores instructions that, when executed on a computer, enable the computer to execute any of the above methods for implementing a robot motion space marker.
According to the method, the risk points influencing the motion of the robot are identified and marked by performing motion simulation on the motion space of the robot on the basis of the planned path according to the service operation requirement of the robot, so that the subsequent planning and layout of the motion path of the robot are facilitated, and the autonomous motion capability and efficiency of the robot are optimized.
Drawings
The above features, technical features, advantages and implementations of the method and apparatus for user equipment admission, the method and apparatus for user equipment handover will be further explained in the following detailed description of preferred embodiments in a clearly understandable manner with reference to the accompanying drawings.
Fig. 1 is a flowchart of a robot motion space marking method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a robot motion space marking apparatus according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a robot according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
For the sake of simplicity, only the parts relevant to the present invention are schematically shown in the drawings, and they do not represent the actual structure as a product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically depicted, or only one of them is labeled. In this document, "a" means not only "only one of this but also a case of" more than one ".
In the development process of autonomous movement of intelligent devices, the inventor needs to utilize some sensors to detect the environment in order to realize the autonomous movement of the intelligent devices. The intelligent device may be an autonomous mobile robot, an autonomous mobile automobile or other autonomous walking device, which may more or less employ a lidar sensor to achieve target object detection, so that the device may achieve barrier-free or obstacle-avoidance movement.
In the field of autonomous mobile robot technology, a 2D lidar sensor is still a sensor frequently selected for use in mobile robot devices to detect surrounding objects.
Due to the variability and randomness of the environment objects in the robot motion space, the requirement on the path planning capability of engineering personnel is improved, so that the simulation of the robot motion environment is provided, the simulation of the robot motion space is further facilitated, and the planning of the robot motion path is facilitated, so that the embodiment of the invention provides the robot motion space marking method.
Referring to fig. 1, a robot motion space marking method according to an embodiment of the present invention includes:
s1, acquiring a detection data frame of a robot in a motion space, and establishing a 3D point cloud map and a 2D map in the motion space according to the detection data frame;
in an embodiment of the present invention, the detection data frame may include a detection data frame obtained by a robot sensor such as a 3D laser radar, for example, a distance, a direction, or a reflection intensity of a target object, or image data obtained by a camera of a robot configuration. And establishing a 3D point cloud map and a 2D map of the robot in a preset motion space by using a 3D laser radar mapping method or a visual mapping method through the detected data frame.
Here, the 3D lidar cloud map is created using data frames describing an environment and a cognitive environment, so that environment information of a current motion space thereof is described through the environment map. Considering that the robot generally walks on a plane route, in order to reduce the calculation amount, a 2D map of the robot on the plane of the movement route is also established at the moment. The 2D map of the robot motion route plane is used as an important parameter of the motion space mark of the embodiment of the invention, so that on one hand, the workload can be reduced, on the other hand, the motion characteristics of the robot are fully considered, and a target object which can be met by the robot under the planar motion route is used as an important reference object.
The embodiment of the invention does not limit the method for constructing the 3D point cloud map of the motion space which the robot can enter and the method for constructing the 2D map of the motion route plane of the robot.
S2, acquiring a first point cloud map below a plane where the robot height is located by using the 3D point cloud map and the robot height;
according to the embodiment of the invention, besides establishing a map of a robot movement route plane, a first point cloud map below the robot height is obtained by combining a 3D point cloud map and robot height data in a robot movement space, and point cloud data in a space above the robot height can be ignored in order to reduce the calculation amount.
S3, determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the robot working data;
the movement route Path is variable due to the need of the robot to actually work, so the starting point and the ending point of the robot movement are firstly determined and the robot movement route is selected in the established 2D map.
In practical robot working scenarios, the planning of the robot movement path can be set manually, for example, in a relatively long autonomous movement path of the robot, by manually setting a predetermined path for the robot, while in some situations, for example, in hospitals, predetermined movement path defining parameters can be set for the robot in an automatic manner, for example, driving to the right in an emergency corridor leaves a corridor for a walking bed. The above information is used as the basis for selecting the movement route of the robot, and is not described herein.
S4, sampling the motion route, and calculating a contour point cloud of the robot on the motion route by combining contour data of the robot;
in the established 2D map, the determined movement route Path is sampled, and simultaneously, the contour point cloud of the robot on the selected route is acquired by combining robot contour data, such as the length, the width and the maximum expansion size data of the robot and new space expansion data generated in left-right rotation, so as to determine the robot contour of the robot in the movement space, and therefore, in the subsequent calculation process of space marks, the influence of a target object of the robot in the movement space on the movement of the robot is possible to be acquired.
And S5, acquiring risk points of robot motion according to the first point cloud map and the contour point cloud, and marking the risk points.
After a point cloud map of the robot below a robot height plane and a contour point cloud in a movement route are obtained, risk points influencing the movement of the robot are obtained through point cloud map data, and meanwhile, the risk points are marked on a 2D map and a 3D point cloud map, so that an important parameter basis is provided for subsequent robot movement path planning.
Preferably, the acquiring the risk points of the robot motion according to the first point cloud map and the contour point cloud, and marking the risk points specifically includes:
acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map;
acquiring a second risk point set of robot movement according to the movement route and the first point cloud map;
marking the first set of risk points and the second set of risk points in a robot motion space.
Preferably, the acquiring the first risk point set of the robot motion according to the contour point cloud and the first point cloud map specifically includes:
traversing each point in the contour point cloud, and obtaining the distance between each point in the contour point cloud and a KD tree constructed according to the first point cloud map;
acquiring a first closest distance from the outline point cloud to the KD tree and a point corresponding to the first closest distance;
when the first closest distance is smaller than a preset first distance threshold, taking a point corresponding to the first closest distance on the contour point cloud as a first risk point;
saving the first risk point in the first risk point set.
Preferably, the acquiring a second risk point set of robot motion according to the motion route and the first point cloud map specifically includes:
acquiring an area of interest within a preset distance range of the movement route where the robot walks on the 2D map;
traversing each point in the region of interest, and acquiring the distance from each point in the region of interest to a KD tree constructed according to the first point cloud map;
acquiring a second closest distance from the KD tree in the region of interest and points corresponding to the second closest distance;
when the second closest distance is smaller than a preset second distance threshold, taking a point corresponding to the second closest distance on the region of interest as a second risk point;
and saving the second risk point in the second risk point set.
In order to achieve the object of the present invention, please refer to fig. 2, an embodiment of the present invention further provides a robot motion space marking apparatus 100, where the apparatus 100 includes:
the map building module 1 is used for building a 3D point cloud map and a 2D map under a motion environment by collecting detection data frames of the robot under the motion environment and according to the detection data frames;
in an embodiment of the present invention, the detection data frame may include a detection data frame obtained by a robot sensor such as a 3D laser radar, for example, a distance, a direction, or a reflection intensity of a target object, or image data obtained by a camera of a robot configuration. And establishing a 3D point cloud map and a 2D map of the robot in a preset motion space by using a 3D laser radar mapping method or a visual mapping method through the detected data frame.
Here, the 3D lidar cloud map is created using data frames describing an environment and a cognitive environment, so that environment information of a current motion space thereof is described through the environment map. Considering that the robot generally walks on a plane route, in order to reduce the calculation amount, a 2D map of the robot on the plane of the movement route is also established at the moment. The 2D map of the robot motion route plane is used as an important parameter of the motion space mark of the embodiment of the invention, so that on one hand, the workload can be reduced, on the other hand, the motion characteristics of the robot are fully considered, and a target object which can be met by the robot under the planar motion route is used as an important reference object.
The embodiment of the invention does not limit the method for constructing the 3D point cloud map of the motion space which the robot can enter and the method for constructing the 2D map of the motion route plane of the robot.
The first point cloud map computing module 2 is used for acquiring a first point cloud map below a plane where the robot height is located by using the 3D point cloud map and the robot height; according to the embodiment of the invention, besides establishing a map of a robot movement route plane, a first point cloud map below the robot height is obtained by combining a 3D point cloud map and robot height data in a robot movement space, and point cloud data in a space above the robot height can be ignored in order to reduce the calculation amount.
The movement route determining module 3 is used for determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the robot working data;
the movement route Path is variable due to the need of the robot to actually work, so the starting point and the ending point of the robot movement are firstly determined and the robot movement route is selected in the established 2D map.
In an actual robot working scenario, the planning selection of the robot movement route can be set manually, for example, in a remote autonomous robot movement journey, by manually setting a predetermined route for the robot, while in some occasions, for example, in a hospital, the robot can be set with predetermined movement route defining parameters in an automatic manner, for example, in an emergency passageway, a passageway is left for a walking bed by driving to the right. The above information is used as the basis for selecting the movement route of the robot, and is not described herein.
The contour point cloud computing module 4 is used for sampling the motion route and computing the contour point cloud of the robot on the motion route by combining robot contour data;
in the established 2D map, the determined movement route Path is sampled, and simultaneously, the contour point cloud of the robot on the selected route is acquired by combining robot contour data, such as the length, the width and the maximum expansion size data of the robot and new space expansion data generated in left-right rotation, so as to determine the robot contour of the robot in the movement space, and therefore, the influence of a target object of the robot in the movement space on the movement of the robot can be acquired in the subsequent calculation process of space marking.
And the motion space marking module 5 is used for acquiring risk points of robot motion according to the first point cloud map and the contour point cloud and marking the risk points.
After a point cloud map of the robot below a robot height plane and contour point clouds in a movement route are obtained, risk points influencing robot movement are obtained through point cloud map data, and meanwhile, the risk points are marked on a 2D map and a 3D point cloud map, so that important parameter basis is provided for subsequent robot movement path planning.
Preferably, the motion space labeling module specifically includes:
the first computing unit is used for acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map;
the second computing unit is used for acquiring a second risk point set of robot motion according to the motion route and the first point cloud map;
a marking unit for marking the first set of risk points and the second set of risk points in a robot motion space.
Preferably, the first calculation unit includes:
a subunit, configured to traverse each point in the contour point cloud, and obtain a distance from each point in the contour point cloud to a KD tree constructed according to the first point cloud map;
a subunit, configured to obtain a first closest distance from the KD tree in the contour point cloud and a point corresponding to the first closest distance;
a subunit, configured to, when the first closest distance is smaller than a preset first distance threshold, take a point on the contour point cloud corresponding to the first closest distance as a first risk point;
a subunit for saving the first risk point in the first set of risk points.
Preferably, the second calculation unit includes:
a sub-unit for obtaining a region of interest within a preset distance range of the movement route traveled by the robot on the 2D map;
a subunit, configured to traverse each point in the region of interest, and obtain a distance from each point in the region of interest to a KD tree constructed according to the first point cloud map;
a subunit, configured to obtain a second closest distance from the KD tree in the region of interest and a point corresponding to the second closest distance;
a subunit, configured to, when the second closest distance is smaller than a preset second distance threshold, take a point on the region of interest corresponding to the second closest distance as a second risk point;
a subunit for saving the second risk point in the second set of risk points.
In order to achieve the object of the present invention, the embodiment of the present invention further provides a computer-readable storage medium, which stores instructions that, when executed on a computer, enable the computer to execute any of the above methods for implementing a robot motion space marker.
According to the method, the risk points influencing the motion of the robot are identified and marked by performing motion simulation on the motion space of the robot on the basis of the planned path according to the service operation requirement of the robot, so that the subsequent planning and layout of the motion path of the robot are facilitated, and the autonomous motion capability and efficiency of the robot are optimized.
It should be noted that the division of each module or unit of the above robot motion space marking apparatus is only a division of logical functions, and may be wholly or partially integrated on one physical entity or physically separated in actual implementation. And these units can be realized in the form of software called by processor; or can be implemented in the form of hardware; and part of the units can be realized in the form of calling by a processor through software, and part of the units can be realized in the form of hardware.
For example, the functions of the above modules or units may be stored in a memory in the form of program codes, which are scheduled by a processor to implement the functions of the above units. The processor may be a general purpose processor such as a Central Processing Unit (CPU) or other processor capable of calling programs. As another example, the above units may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), etc. For another example, in combination with the above two methods, part of the functions is implemented in the form of a scheduler code of the processor, and part of the functions is implemented in the form of a hardware integrated circuit. And when the above functions are integrated together, the functions can be realized in the form of System-On-a-Chip (SOC).
The robot motion space marking device provided by the embodiment of the application can be specifically a chip, and the chip comprises: a processing unit, which may be, for example, a processor, and a communication unit, which may be, for example, an input/output interface, a pin or a circuit, etc. The processing unit may execute computer-executable instructions stored by the memory unit to cause a chip within the robotic motion space marking apparatus to perform the steps performed by the robotic motion space marking apparatus described in the illustrated embodiment described above, or to cause a chip within the execution device to perform the steps performed by the robotic motion space marking apparatus described in the illustrated embodiment of fig. 2 described above.
Optionally, the storage unit is a storage unit in the chip, such as a register, a cache, and the like, and the storage unit may also be a storage unit located outside the chip in the wireless access device, such as a read-only memory (ROM) or another type of static storage device that can store static information and instructions, a Random Access Memory (RAM), and the like.
In order to achieve the object of the present invention, an embodiment of the present invention further provides a robot 180, which may include the robot motion space marking apparatus as described above.
The robot 180 may further include a processor 1803 and a memory 1804, the processor 1803 coupled to the memory 1804, wherein,
the memory 1804 is used for storing programs;
the processor 1803 is configured to execute the program in the memory, so that the robot performs the method for marking the robot motion space as described above.
Referring to fig. 3, the method disclosed in the embodiment of the present invention and corresponding to fig. 1 may be applied to an autonomous mobile robot 180, where the robot 180 includes a processor 1803, and the processor 1803 may be an integrated circuit chip having signal processing capability. In implementation, the steps of the above method may be implemented by integrated logic circuits of hardware or instructions in the form of software in the processor 1803. The processor 1803 may be a general-purpose processor, a Digital Signal Processor (DSP), a microprocessor or a microcontroller, and may further include an Application Specific Integrated Circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The processor 1803 may implement or perform the methods, steps, and logic blocks disclosed in the embodiments corresponding to fig. 1 of the present application.
A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 1804, and the processor 1803 reads the information in the memory 1804, and completes the steps of the above method in combination with the hardware thereof.
The receiver 1801 may be used to receive entered numeric or character information and generate signal inputs related to settings and function controls associated with the robotic motion space marking apparatus 100. The transmitter 1802 may be used to output numeric or character information through a first interface; the transmitter 1802 may also be used to send instructions to the disk groups through the first interface to modify data in the disk groups; the transmitter 1802 may also include a display device such as a display screen.
An embodiment of the present invention further provides a computer-readable storage medium, in which a program for signal processing is stored, and when the program runs on a computer, the computer is enabled to execute the steps executed by the robot motion space marking method described in the foregoing illustrated embodiment, or the computer is enabled to execute the steps executed by the robot motion space marking apparatus described in the foregoing illustrated embodiment of fig. 2.
It should be noted that the above-described embodiments of the apparatus are merely schematic, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiments of the apparatus provided in the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus necessary general-purpose hardware, and certainly can also be implemented by special-purpose hardware including special-purpose integrated circuits, special-purpose CPUs, special-purpose memories, special-purpose components and the like. Generally, functions performed by computer programs can be easily implemented by corresponding hardware, and specific hardware structures for implementing the same functions may be various, such as analog circuits, digital circuits, or dedicated circuits. However, for the present application, the implementation of a software program is more preferable. Based on such understanding, the technical solutions of the present application may be substantially embodied in or contributed to by the prior art, and the computer software product may be stored in a readable storage medium, such as a floppy disk, a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk or an optical disk of a computer, and includes several instructions for causing a computer device (which may be a personal computer or a network device) to execute the method according to the embodiments of the present application.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, which may be any available medium that a computer can store or a data storage device, such as a training device, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It should be noted that the above embodiments can be freely combined as necessary. The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (6)
1. A robot motion space marking method is characterized by comprising the following steps:
acquiring a detection data frame of a robot in a motion space, and establishing a 3D point cloud map and a 2D map in the motion space according to the detection data frame;
acquiring a first point cloud map below a plane where the robot height is located by using the 3D point cloud map and the robot height;
determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the working data of the robot;
sampling the motion route, and calculating a contour point cloud of the robot on the motion route by combining robot contour data;
acquiring risk points of robot motion according to the first point cloud map and the contour point cloud, and marking the risk points; wherein the content of the first and second substances,
the acquiring of the risk points of the robot motion according to the first point cloud map and the contour point cloud, and the marking of the risk points specifically comprises:
acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map;
acquiring a second risk point set of robot movement according to the movement route and the first point cloud map;
marking the first set of risk points and the second set of risk points in a robot motion space;
the step of acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map specifically comprises the following steps:
traversing each point in the contour point cloud, and obtaining the distance between each point in the contour point cloud and a KD tree constructed according to the first point cloud map;
acquiring a first closest distance from the outline point cloud to the KD tree and a point corresponding to the first closest distance;
when the first closest distance is smaller than a preset first distance threshold, taking a point corresponding to the first closest distance on the contour point cloud as a first risk point;
saving the first risk point in the first set of risk points.
2. The method for marking the motion space of the robot according to claim 1, wherein the step of obtaining the second set of risk points of the motion of the robot according to the motion route and the first point cloud map specifically comprises:
acquiring an area of interest within a preset distance range of the movement route where the robot walks on the 2D map;
traversing each point in the region of interest, and acquiring the distance from each point in the region of interest to a KD tree constructed according to the first point cloud map;
acquiring a second closest distance from the KD tree in the region of interest and a point corresponding to the second closest distance;
when the second closest distance is smaller than a preset second distance threshold, taking a point corresponding to the second closest distance on the region of interest as a second risk point;
and saving the second risk point in the second risk point set.
3. A robotic motion space marking apparatus, comprising:
the map building module is used for building a 3D point cloud map and a 2D map under the motion environment by collecting detection data frames of the robot under the motion environment and according to the detection data frames;
the first point cloud map computing module is used for acquiring a first point cloud map below the plane where the robot height is located by utilizing the 3D point cloud map and the robot height;
the movement route determining module is used for determining a starting point, an end point and a movement route of the robot movement on the 2D map according to the robot working data;
the contour point cloud computing module is used for sampling the movement route and computing a contour point cloud of the robot on the movement route by combining robot contour data;
the motion space marking module is used for acquiring risk points of robot motion according to the first point cloud map and the contour point cloud and marking the risk points; wherein, the motion space marking module specifically comprises:
the first computing unit is used for acquiring a first risk point set of robot motion according to the contour point cloud and the first point cloud map;
the second computing unit is used for acquiring a second risk point set of robot motion according to the motion route and the first point cloud map;
a marking unit for marking the first risk point set and the second risk point set in a robot motion space;
the first calculation unit includes:
a subunit, configured to traverse each point in the contour point cloud, and obtain a distance from each point in the contour point cloud to a KD tree constructed according to the first point cloud map;
a subunit, configured to obtain a first closest distance from the KD tree in the contour point cloud and a point corresponding to the first closest distance;
a subunit, configured to, when the first closest distance is smaller than a preset first distance threshold, take a point on the contour point cloud corresponding to the first closest distance as a first risk point;
a subunit for saving the first risk point in the first set of risk points.
4. The robotic motion space marking apparatus of claim 3, wherein the second computing unit comprises:
a sub-unit for obtaining a region of interest within a preset distance range of the movement route traveled by the robot on the 2D map;
a subunit, configured to traverse each point in the region of interest, and obtain a distance from each point in the region of interest to a KD tree constructed according to the first point cloud map;
a subunit, configured to obtain a second closest distance from the KD tree in the region of interest and a point corresponding to the second closest distance;
a subunit, configured to, when the second closest distance is smaller than a preset second distance threshold, take a point on the region of interest corresponding to the second closest distance as a second risk point;
a subunit for saving the second risk point in the second set of risk points.
5. A robot comprising a processor and a memory, the processor being coupled with the memory,
the memory is used for storing programs;
the processor to execute the program in the memory to cause the robot to perform the method of any of claims 1-2.
6. A computer storage medium, comprising a program which, when run on a computer, causes the computer to perform the method of any one of claims 1-2.
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