Robot motion deceleration method, system and equipment and storage medium

Abstract

The invention provides a robot motion deceleration method, system and device and a storage medium, and the method comprises the steps: obtaining the point cloud data of a target object, and collecting the point cloud data through a depth camera after the target object is sucked up by an end effector; determining the area of at least one side surface of the target object according to the point cloud data, and obtaining an area threshold value corresponding to the target object at least according to the area of the side surface; and a first speed coefficient is determined according to the area threshold value, and the running speed of the robot is determined according to the first speed coefficient. Compared with the prior art, the large area threshold value corresponds to the large first speed coefficient, the small area threshold value corresponds to the small first speed coefficient, the running speed of the robot is determined according to the first speed coefficients, and therefore the phenomenon that the target object falls off due to the fact that the moving speed of the robot is too high when the target object is carried is avoided.

Description

Background Art

[0002] An industrial robot is an intelligent device equipped with sensors, objective lenses and electronic optical systems that can quickly sort and move goods.

[0003] More and more visual sensors and force sensors will be used in industrial robots, and industrial robots will become more and more intelligent. With the advancement of sensing and recognition systems, artificial intelligence and other technologies, robots are moving from being controlled in one direction to storing and applying data by themselves, and are gradually becoming information-based.

[0004] When an industrial robot is used to sort and carry goods, it is necessary to collect images of the goods through a visual sensor, identify the image of the goods to determine the posture of the goods, and then the industrial robot picks or carries the goods through a loaded clamp or suction cup. In the prior art, when sorting and carrying goods of different volumes and masses, the movement speed of the robot is generally constant, which will cause some target objects to fall due to their own suction position, volume and weight during transportation due to the robot's excessive movement speed, which not only easily causes damage to the goods, but also may cause safety risks. Summary of the invention

[0005] In view of the defects in the prior art, an object of the present invention is to provide a robot motion deceleration method, system, device and storage medium.

[0006] The robot motion deceleration method provided by the present invention comprises the following steps:

[0007] Step S1: acquiring point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector;

[0008] Step S2: determining the area of ​​at least one side surface of the target object according to the point cloud data, and obtaining an area threshold corresponding to the target object according to at least the area of ​​the side surface;

[0009] Step S3: determining a first speed coefficient according to the area threshold, and determining the running speed of the robot according to the first speed coefficient.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S101: controlling the end effector to absorb a target object and move it to a target position, wherein the target position is within the imaging field of view of the depth camera;

[0012] Step S102: controlling the depth camera to collect a depth image of the target object from an upward perspective, wherein the depth image at least includes the bottom and side depths of the target object;

[0013] Step S103: reconstructing and generating point cloud data according to the depth image.

[0014] Preferably, step S2 comprises the following steps:

[0015] Step S2011: determining a point cloud normal according to the point cloud data, wherein the point cloud normal is in the same direction as the axial direction of the end effector;

[0016] Step S2012: obtaining a preset deviation threshold, deleting the point cloud data whose deviation distance along the direction of the point cloud normal vector is greater than the deviation threshold to generate target point cloud data;

[0017] Step S2013: fitting the extension range of the bottom and side surfaces of the target object according to the target point cloud data, and determining the area of ​​the bottom and side surfaces of the target object according to the extension range.

[0018] Preferably, the target object is in a cubic shape and the end effector is a suction cup, and step S2 comprises the following steps:

[0019] Step S2021: acquiring the end surface coordinates of the end effector, and determining the height distance between the bottom side surface of the target object and the end effector according to the end surface coordinates;

[0020] Step S2022: acquiring an extension range of the bottom side surface, and determining a length and a width of the bottom side surface according to the extension range;

[0021] Step S2023: determining, according to the length, the width, and the height distance, that the bottom side of the target object is the largest side, the second largest side, or the smallest side of the target object;

[0022] Step S2024: Determine a corresponding area threshold according to whether the bottom side surface is the largest side surface, the second largest side surface or the smallest side surface of the target object.

[0023] Preferably, in step S3, when the area threshold is determined according to the largest side of the target object, the first speed coefficient is the largest;

[0024] When the area threshold is determined based on the second largest side of the target object, the first speed coefficient is the second largest;

[0025] When the area threshold is determined according to the smallest side of the target object, the first speed coefficient is the smallest.

[0026] Preferably, step S3 comprises the following steps:

[0027] Step S301: determining the center of gravity of the bottom and side surfaces according to the target point cloud data;

[0028] Step S302: Acquire the end face coordinates of the end effector, and determine a first distance and a second distance between the center of gravity of the bottom side surface and the center of the end effector according to the end face coordinates, wherein the first distance is the distance in the length direction of the bottom side surface, and the second distance is the distance in the width direction of the bottom side surface;

[0029] Step S303: When the first distance is greater than a preset first distance threshold and / or the second distance is greater than a preset second distance threshold, a second speed coefficient is generated according to the first speed coefficient, and the running speed of the robot is determined according to the second speed coefficient.

[0030] Preferably, step S3 comprises the following steps:

[0031] Step S301: collecting and determining weight data of the target object through a weight sensor;

[0032] Step S302: judging whether the item is multiple-grabbed according to the area threshold and the weight data, and when it is judged that the item is multiple-grabbed according to the area threshold and / or the weight data, determining the first speed coefficient according to the area threshold and the weight data;

[0033] Step S303: Determine the running speed of the robot according to the first speed coefficient.

[0034] The robot motion deceleration method provided by the present invention comprises the following steps:

[0035] Step M1: acquiring point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector;

[0036] Step M2: determining a hexahedral bounding box of the target object according to the point cloud data, and determining the length, width and center point of the grasping surface of the target object based on the bounding box;

[0037] Step M3: Obtain the end face coordinates of the end effector, determine the deviation between the grasping point and the center point of the grasping surface and / or the ratio of the length to the width according to the end face coordinates to determine a first speed coefficient, and determine the running speed of the robot according to the first speed coefficient.

[0038] The robot motion deceleration system provided by the present invention comprises the following modules:

[0039] A data acquisition module, used to acquire point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector;

[0040] A threshold acquisition module, used to determine the area of ​​at least one side of the target object according to the point cloud data, and to acquire an area threshold corresponding to the target object according to at least the area of ​​the side;

[0041] The speed determination module determines a first speed coefficient according to the area threshold, and determines the running speed of the robot according to the first speed coefficient.

[0042] The robot motion deceleration device provided by the present invention comprises:

[0043] processor;

[0044] a memory module in which executable instructions of the processor are stored;

[0045] Wherein, the processor is configured to perform the steps of the robot motion deceleration method by executing the executable instructions.

[0046] The computer-readable storage medium provided according to the present invention is used to store a program, and when the program is executed, the steps of the robot motion deceleration method are implemented.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] In the present invention, point cloud data of the target object is obtained, the area of ​​at least one side of the target object is determined based on the point cloud data, the area threshold corresponding to the target object is obtained based on at least the area of ​​the side, and the corresponding first speed coefficient is determined based on the area threshold, wherein a larger area threshold corresponds to a larger first speed coefficient, and a smaller area threshold corresponds to a smaller first speed coefficient. The running speed of the robot is determined based on the first speed coefficient, thereby avoiding the target object from falling due to the excessively fast movement speed of the robot during transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings in the following descriptions are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without creative work. By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, purposes and advantages of the present invention will become more obvious:

[0050] Figure 1A flowchart of the steps of the robot motion deceleration method in an embodiment of the present invention;

[0051] Figure 2 A flowchart of the steps of collecting point cloud data in an embodiment of the present invention;

[0052] Figure 3 A flowchart of the steps of determining the area of ​​the bottom and side surfaces of an object according to point cloud data in an embodiment of the present invention;

[0053] Figure 4 This is a flowchart of the steps of obtaining the area threshold corresponding to the object in an embodiment of the present invention;

[0054] Figure 5 A flowchart of the steps for determining the running speed of a robot in an embodiment of the present invention;

[0055] Figure 6 A flowchart of the steps for determining the running speed of the robot in a modified example of the present invention;

[0056] Figure 7 This is a schematic diagram of determining whether an object is grasped multiple times in an embodiment of the present invention;

[0057] Figure 8 This is a schematic diagram of a module of a robot motion deceleration system according to an embodiment of the present invention;

[0058] Fig. 9 It is a schematic diagram of the structure of a robot motion deceleration device in an embodiment of the present invention;

[0059] Fig.10 is a schematic diagram of the structure of an item picking system in an embodiment of the present invention, and

[0060] Fig.11 Schematic diagram of the structure of a computer-readable storage medium in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0062] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0063] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0064] The following specific embodiments are used to describe in detail the technical solutions of the present invention and how the technical solutions of the present application solve the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0065] Figure 1 FIG. 1 is a flow chart of the steps of the robot motion deceleration method according to an embodiment of the present invention. Figure 1 As shown, the robot motion deceleration method provided by the present invention is used for the robot to pick items, and the robot includes a weight sensor, an end effector and a depth camera, and includes the following steps:

[0066] Step S1: acquiring point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector;

[0067] In an embodiment of the present invention, the point cloud data is a data set, each point in the data set represents a set of X, Y, Z geometric coordinates and an intensity value, which records the intensity of the return signal according to the reflectivity of the object surface. When these points are combined together, a point cloud is formed, that is, a collection of data points representing a 3D shape or object in space. The point cloud can also be automatically colored to achieve more realistic visualization.

[0068] Figure 2 FIG. 1 is a flowchart of the steps of collecting point cloud data in an embodiment of the present invention. Figure 2 As shown, step S1 includes the following steps:

[0069] Step S101: controlling the end effector to absorb a target object and move it to a target position, wherein the target position is within the imaging field of view of the depth camera;

[0070] Step S102: controlling the depth camera to collect a depth image of the target object from an upward perspective, wherein the depth image at least includes the bottom and side depths of the target object;

[0071] Step S103: reconstructing and generating point cloud data according to the depth image.

[0072] In the embodiment of the present invention, the end effector is connected to the mechanical arm of the robot via the weight sensor, so that the weight data of the object can be obtained when the end effector sucks up the object.

[0073] The target position is related to the position where the depth camera and the end effector suck and place the object, so that the depth camera can at least cover the bottom and side surfaces of the object to collect the point cloud of the bottom and side surfaces of the object.

[0074] Step S2: determining the area of ​​at least one side surface of the target object according to the point cloud data, and obtaining an area threshold corresponding to the target object according to at least the area of ​​the side surface;

[0075] Figure 3 FIG. 1 is a flowchart of the steps of determining the area of ​​the bottom and side surfaces of an object according to point cloud data in an embodiment of the present invention. Figure 3 As shown, when the area of ​​at least one side of the object is determined according to the point cloud data, and the side is the bottom side, the step S2 includes the following steps:

[0076] Step S2011: determining a point cloud normal according to the point cloud data, wherein the point cloud normal is in the same direction as the axial direction of the end effector;

[0077] Step S2012: obtaining a preset deviation threshold, deleting the point cloud data whose deviation distance along the direction of the point cloud normal vector is greater than the deviation threshold to generate target point cloud data;

[0078] Step S2013: fitting the extension range of the bottom and side surfaces of the target object according to the target point cloud data, and determining the area of ​​the bottom and side surfaces of the target object according to the extension range.

[0079] Each point in the point cloud data includes the XYZ coordinates of the point in the camera coordinate system. The point cloud data located on at least one side of the object will have a range in one coordinate direction. For example, the fluctuation of the point cloud on the bottom side of the object in the axial direction of the end effector will be within a certain range, and the point cloud on the other sides of the object will significantly deviate from the point cloud on the bottom side. Therefore, a deviation threshold can be set to filter out the point cloud on the other sides of the object. The deviation threshold can be set according to the height of the object along the axial direction of the end effector, such as one tenth of the height.

[0080] Since the fluctuation of the point cloud on the bottom side of the object in the axial direction of the end effector will be within a certain range, the point cloud on the bottom side of the object can be fitted to determine the range and area of ​​the bottom side of the object.

[0081] Figure 4 FIG. 1 is a flowchart of the steps of obtaining the area threshold corresponding to the item in an embodiment of the present invention. Figure 4 As shown, when the object is in a cubic shape and the end effector is a suction cup, at least when the area threshold corresponding to the object is obtained based on the area, the step S2 includes the following steps:

[0082] Step S2021: acquiring the end surface coordinates of the end effector, and determining the height distance between the bottom side surface of the target object and the end effector according to the end surface coordinates;

[0083] Step S2022: acquiring an extension range of the bottom side surface, and determining a length and a width of the bottom side surface according to the extension range;

[0084] Step S2023: determining, according to the length, the width, and the height distance, that the bottom side of the target object is the largest side, the second largest side, or the smallest side of the target object;

[0085] Step S2024: Determine a corresponding area threshold according to whether the bottom side surface is the largest side surface, the second largest side surface or the smallest side surface of the target object.

[0086] In an embodiment of the present invention, the end face coordinates of the end effector are the lower end face coordinates of the suction cup, which can be obtained by the robot. The coordinates of the bottom side of the object can be determined by point cloud fitting, and the coordinate difference along the axial direction of the end effector can generate the height distance between the bottom side of the object and the end effector.

[0087] For a cubic object, which has three sides a, b, and c, where a>b>c, the largest side is the side formed by sides a and b, the second largest side is the side formed by sides a and c, and the smallest side is the side formed by sides b and c.

[0088] When the bottom side is the largest side of the article, the length of the bottom side is a, the width is b, and the height is c, or the length of the bottom side is a, the width is 2b, and the height is c, or the length of the bottom side is 2a, the width is b, and the height is c;

[0089] When the bottom side is the second largest side of the article, the length of the bottom side is a, the width is c, and the height is b, or the length of the bottom side is 2a, the width is c, and the height is b, or the length of the bottom side is a, the width is 2c, and the height is b;

[0090] When the bottom side is the smallest side of the article, the length of the bottom side is b, the width is c, and the height is a, or the length of the bottom side is 2b, the width is c, and the height is a, or the length of the bottom side is b, the width is 2c, and the height is a.

[0091] The area threshold is the area of ​​the bottom and side surfaces×the coefficient, and the coefficient can take any value between 0.8 and 1.

[0092] The height threshold may be determined by the height corresponding to the bottom side surface of the object at this time, and may be set to be between 0.8 and 1 of the height.

[0093] Step S3: determining a first speed coefficient according to the area threshold, and determining the running speed of the robot according to the first speed coefficient.

[0094] In an embodiment of the present invention, when the area threshold is determined according to the largest side of the target object, the first speed coefficient is the largest;

[0095] When the area threshold is determined based on the second largest side of the target object, the first speed coefficient is the second largest;

[0096] When the area threshold is determined according to the smallest side of the target object, the first speed coefficient is the smallest.

[0097] Figure 5 FIG. 1 is a flow chart of the steps for determining the running speed of the robot in an embodiment of the present invention. Figure 5 As shown, step S3 includes the following steps:

[0098] Step S301: determining the center of gravity of the bottom and side surfaces according to the target point cloud data;

[0099] Step S302: Acquire the end face coordinates of the end effector, and determine a first distance and a second distance between the center of gravity of the bottom side surface and the center of the end effector according to the end face coordinates, wherein the first distance is the distance in the length direction of the bottom side surface, and the second distance is the distance in the width direction of the bottom side surface;

[0100] Step S303: When the first distance is greater than a preset first distance threshold and / or the second distance is greater than a preset second distance threshold, a second speed coefficient is generated according to the first speed coefficient, and the running speed of the robot is determined according to the second speed coefficient.

[0101] Figure 6 FIG. 1 is a flow chart of the steps for determining the running speed of the robot in a modified example of the present invention, as shown in FIG. Figure 6 As shown, step S3 includes the following steps:

[0102] Step S301: collecting and determining weight data of the target object through a weight sensor;

[0103] Step S302: judging whether the item is multiple-grabbed according to the area threshold and the weight data, and when it is judged that the item is multiple-grabbed according to the area threshold and / or the weight data, determining the first speed coefficient according to the area threshold and the weight data;

[0104] Step S303: Determine the running speed of the robot according to the first speed coefficient.

[0105] In the embodiment of the present invention, the weight threshold can be set to be more than 1.2 times the weight of the object, but the weight sensor generally has a certain accuracy range. The weight sensor commonly used in grasping is not sensitive to light objects, such as objects under 20g. At this time, if the weight sensor is replaced, the entire fixture needs to be disassembled and replaced, which is time-consuming and labor-intensive, and will also increase the cost of use for the end user. Therefore, for some small weight objects, an auxiliary method of judging by area is added.

[0106] In the embodiment of the present invention, when the area of ​​the bottom side surface is greater than the area threshold corresponding to the largest side surface, it is considered that there is multiple grasping, and in this case, the bottom side surface is determined to be the largest side surface of the object;

[0107] When the bottom side surface is larger than the area threshold corresponding to the second largest side surface and the height distance is larger than the height threshold corresponding to the second largest side surface, it is considered that multiple grasping occurs. At this time, when the bottom side surface is determined to be the second largest side surface of the object,;

[0108] When the bottom side surface is larger than the area threshold corresponding to the smallest side surface and the height distance is larger than the height threshold corresponding to the smallest side surface, it is considered as multiple grasping, and the bottom side surface is determined to be the smallest side surface of the object.

[0109] When the bottom side is not the largest side of the object, it is necessary to add the height distance judgment to prevent the situation where the area between two overlapping objects is smaller than the area threshold corresponding to the largest side, resulting in a misjudgment. For example, if the size of an object is 3×2×1 and the bottom side is detected to be 5, it may be a 3×2 bottom side or two 2×1 bottom sides placed side by side with a height of 3. Therefore, it is necessary to check the height to see if there is a situation of multiple grasping.

[0110] Figure 7 This is a schematic diagram of the situation of judging whether an item has multiple grasps in an embodiment of the present invention. The situation where the area of ​​the bottom side surface is greater than the area threshold corresponding to the largest side surface is shown in Figures (c) and (d), the situation where the bottom side surface is greater than the area threshold corresponding to the second largest side surface and the height distance is greater than the height threshold corresponding to the second largest side surface is shown in Figures (e) and (f), and the situation where the bottom side surface is greater than the area threshold corresponding to the smallest side surface and the height distance is greater than the height threshold corresponding to the smallest side surface is shown in Figures (a) and (b).

[0111] The robot motion deceleration method provided by the present invention comprises the following steps:

[0112] Step M1: acquiring point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector;

[0113] Step M2: determining a hexahedral bounding box of the target object according to the point cloud data, and determining the length, width and center point of the grasping surface of the target object based on the bounding box;

[0114] Step M3: Obtain the end face coordinates of the end effector, determine the deviation between the grasping point and the center point of the grasping surface and / or the ratio of the length to the width according to the end face coordinates to determine a first speed coefficient, and determine the running speed of the robot according to the first speed coefficient.

[0115] In the embodiment of the present invention, the larger the ratio of the length to the width, the smaller the first speed coefficient, and the larger the deviation between the grasping point and the center point of the grasping surface, the smaller the first speed coefficient;

[0116] In addition, when the weight data of the target object is collected by the weight sensor, when the weight data is greater than a preset weight data threshold, the greater the weight data, the smaller the first speed coefficient.

[0117] Figure 8 FIG. 1 is a schematic diagram of a module of a robot motion deceleration system according to an embodiment of the present invention. Figure 8 As shown, the robot motion deceleration system provided by the present invention includes the following modules:

[0118] A data acquisition module, used to acquire point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector;

[0119] A threshold acquisition module, used to determine the area of ​​at least one side of the target object according to the point cloud data, and to acquire an area threshold corresponding to the target object according to at least the area of ​​the side;

[0120] The speed determination module determines a first speed coefficient according to the area threshold, and determines the running speed of the robot according to the first speed coefficient.

[0121] The present invention also provides a robot motion deceleration device, comprising a processor and a memory, wherein the memory stores executable instructions of the processor, wherein the processor is configured to execute the robot motion deceleration method steps by executing the executable instructions.

[0122] As described above, in this embodiment, point cloud data of the target object is obtained, the area of ​​at least one side of the target object is determined according to the point cloud data, the area threshold corresponding to the target object is obtained at least according to the area of ​​the side, and the corresponding first speed coefficient is determined according to the area threshold, wherein a larger area threshold corresponds to a larger first speed coefficient, and a smaller area threshold corresponds to a smaller first speed coefficient, and the running speed of the robot is determined according to the first speed coefficient, thereby avoiding the target object from falling due to the robot's excessive movement speed during transportation.

[0123] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits", "modules" or "platforms".

[0124] Fig. 9 Schematic diagram of the structure of the robot motion deceleration device in the embodiment of the present invention. Fig. 9 The electronic device 600 according to this embodiment of the present invention is described. Fig. 9 The electronic device 600 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0125] like Fig. 9 As shown, the electronic device 600 is in the form of a general computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0126] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 executes the steps of various exemplary embodiments of the present invention described in the robot motion deceleration method section of this specification. For example, the processing unit 610 can execute the following steps: Figure 1 Follow the steps shown in .

[0127] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0128] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0129] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0130] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, cameras, depth cameras, etc.), one or more devices that enable a user to interact with the electronic device 600, and / or any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed through an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 through the bus 630. It should be understood that although Fig. 9Not shown, other hardware and / or software modules may be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0131] Fig.10 FIG. 1 is a schematic diagram of the structure of an article picking system in an embodiment of the present invention. The robot motion deceleration device can be configured as a part or the entire article picking system. Fig.10 As shown, the article picking system provided by the present invention further includes:

[0132] The first unit and the second unit are used for storing and / or transporting materials;

[0133] A depth camera 300, whose visual scanning area covers at least the first unit of storage or transportation of the material, is used to visually scan the material, collect a depth image of the material, and generate posture information of the material according to the depth image;

[0134] The robot unit 100 is in communication connection with the depth camera 300, and is used for receiving the position information, and grasping the material with a corresponding grasping posture according to the position information and then transferring it to the second unit.

[0135] The robot unit 100 includes a suction cup 101 , a weight sensor 102 , and a vertical flexible mechanism 103 ;

[0136] The suction cup 101 is sleeved on the vertical flexible mechanism 103 through the weight sensor 102, and the vertical flexible mechanism 103 is installed on the robot arm, so that the weight data of the object can be obtained when the suction cup 101 sucks up the object. The vertical flexible mechanism 103 is a sleeve structure.

[0137] Wherein, the robot unit 100 includes the above-mentioned processor, and the above-mentioned processor is configured to execute the robot motion deceleration method steps by executing executable instructions to obtain point cloud data of the target object, determine the area of ​​at least one side of the target object according to the point cloud data, obtain the area threshold corresponding to the target object at least according to the area of ​​the side, and determine the corresponding first speed coefficient according to the area threshold, wherein a larger area threshold corresponds to a larger first speed coefficient, and a smaller area threshold corresponds to a smaller first speed coefficient, and the running speed of the robot is determined according to the first speed coefficient, thereby avoiding the target object from falling due to the robot's excessive movement speed during transportation.

[0138] In one embodiment of the present invention, the first unit may be configured as a storage unit 200 and a feeding unit;

[0139] The material storage unit 200 is used to store materials;

[0140] A feeding unit, used for transporting the storage unit 200;

[0141] The robot unit 100 is in communication connection with the depth camera 300, and is used for receiving the position information, and grasping the material with a corresponding grasping posture according to the position information and then transferring it to the second unit.

[0142] The second unit may be configured to transport or store the sorted materials.

[0143] In an embodiment of the present invention, a computer-readable storage medium is also provided for storing a program, and the steps of the robot motion deceleration method are implemented when the program is executed. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary embodiments of the present invention described in the robot motion deceleration method section above in this specification.

[0144] As shown above, when the program of the computer-readable storage medium of this embodiment is executed, point cloud data of the target object is obtained, the area of ​​at least one side of the target object is determined based on the point cloud data, an area threshold corresponding to the target object is obtained based on at least the area of ​​the side, and a corresponding first speed coefficient is determined based on the area threshold, wherein a larger area threshold corresponds to a larger first speed coefficient, and a smaller area threshold corresponds to a smaller first speed coefficient, and the running speed of the robot is determined based on the first speed coefficient, thereby avoiding the target object from falling due to the robot's excessive movement speed during transportation.

[0145] Fig.11 Schematic diagram of the structure of a computer-readable storage medium in an embodiment of the present invention. Fig.11 As shown, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0146] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0147] Computer readable storage media may include data signals propagated in baseband or as part of a carrier wave, wherein readable program codes are carried. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program codes contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0148] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0149] In an embodiment of the present invention, point cloud data of a target object is obtained, the area of ​​at least one side of the target object is determined based on the point cloud data, an area threshold corresponding to the target object is obtained based on at least the area of ​​the side, and a corresponding first speed coefficient is determined based on the area threshold, wherein a larger area threshold corresponds to a larger first speed coefficient, and a smaller area threshold corresponds to a smaller first speed coefficient. The running speed of the robot is determined based on the first speed coefficient, thereby preventing the target object from falling due to the robot's excessive movement speed during transportation.

[0150] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other. The above description of the disclosed embodiments enables professionals and technicians in this field to implement or use the present invention. Various modifications to these embodiments will be obvious to professionals and technicians in this field, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this article, but will comply with the widest range consistent with the principles and novel features disclosed herein.

[0151] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art may make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A robot motion deceleration method, characterized in that: The steps include: Step S1: acquiring point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector; Step S2: determining the area of ​​at least one side surface of the target object according to the point cloud data, and obtaining an area threshold corresponding to the target object according to at least the area of ​​the side surface; Step S3: determining a first speed coefficient according to the area threshold, and determining the running speed of the robot according to the first speed coefficient.

2. The robot motion deceleration method according to claim 1, characterized in that: The step S1 comprises the following steps: Step S101: controlling the end effector to absorb a target object and move it to a target position, wherein the target position is within the imaging field of view of the depth camera; Step S102: controlling the depth camera to collect a depth image of the target object from an upward perspective, wherein the depth image at least includes the bottom and side depths of the target object; Step S103: reconstructing and generating point cloud data according to the depth image.

3. The robot motion deceleration method according to claim 2, characterized in that: The step S2 comprises the following steps: Step S2011: determining a point cloud normal according to the point cloud data, wherein the point cloud normal is in the same direction as the axial direction of the end effector; Step S2012: obtaining a preset deviation threshold, deleting the point cloud data whose deviation distance along the direction of the point cloud normal vector is greater than the deviation threshold to generate target point cloud data; Step S2013: fitting the extension range of the bottom and side surfaces of the target object according to the target point cloud data, and determining the area of ​​the bottom and side surfaces of the target object according to the extension range.

4. The robot motion deceleration method according to claim 3, characterized in that: The target object is in a cubic shape and the end effector is a suction cup, and step S2 comprises the following steps: Step S2021: acquiring the end surface coordinates of the end effector, and determining the height distance between the bottom side surface of the target object and the end effector according to the end surface coordinates; Step S2022: acquiring an extension range of the bottom side surface, and determining a length and a width of the bottom side surface according to the extension range; Step S2023: determining, according to the length, the width, and the height distance, that the bottom side of the target object is the largest side, the second largest side, or the smallest side of the target object; Step S2024: Determine a corresponding area threshold according to whether the bottom side surface is the largest side surface, the second largest side surface or the smallest side surface of the target object.

5. The robot motion deceleration method according to claim 4, characterized in that: In step S3, when the area threshold is determined according to the largest side of the target object, the first speed coefficient is maximum; When the area threshold is determined based on the second largest side of the target object, the first speed coefficient is the second largest; When the area threshold is determined according to the smallest side of the target object, the first speed coefficient is minimum.

6. The robot motion deceleration method according to claim 1, characterized in that: The step S3 comprises the following steps: Step S301: determining the center of gravity of the bottom and side surfaces according to the target point cloud data; Step S302: Acquire the end face coordinates of the end effector, and determine a first distance and a second distance between the center of gravity of the bottom side surface and the center of the end effector according to the end face coordinates, wherein the first distance is the distance in the length direction of the bottom side surface, and the second distance is the distance in the width direction of the bottom side surface; Step S303: When the first distance is greater than a preset first distance threshold and / or the second distance is greater than a preset second distance threshold, a second speed coefficient is generated according to the first speed coefficient, and the running speed of the robot is determined according to the second speed coefficient.

7. A robot motion deceleration method, characterized in that: The steps include: Step M1: acquiring point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector; Step M2: determining a hexahedral bounding box of the target object according to the point cloud data, and determining the length, width and center point of the grasping surface of the target object based on the bounding box; Step M3: Obtain the end face coordinates of the end effector, determine the deviation between the grasping point and the center point of the grasping surface and / or the ratio of the length to the width according to the end face coordinates to determine a first speed coefficient, and determine the running speed of the robot according to the first speed coefficient.

8. A robot motion deceleration system, characterized in that: Includes the following modules: A data acquisition module, used to acquire point cloud data of a target object, wherein the point cloud data is collected by a depth camera after the target object is sucked up by an end effector; A threshold acquisition module, used to determine the area of ​​at least one side of the target object according to the point cloud data, and to acquire an area threshold corresponding to the target object according to at least the area of ​​the side; The speed determination module determines a first speed coefficient according to the area threshold, and determines the running speed of the robot according to the first speed coefficient.

9. A robot motion deceleration device, characterized in that: include: processor; a memory module in which executable instructions of the processor are stored; Wherein, the processor is configured to perform the steps of the robot motion deceleration method according to any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium for storing a program, characterized in that: When the program is executed, the steps of the robot motion deceleration method according to any one of claims 1 to 7 are implemented.

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