Body-aware robot, material transfer method, storage medium, and program product

Abstract

The application relates to the technical field of workshop material transfer, in particular to a body intelligent robot, a material transfer method, a storage medium and a program product. The method comprises the following steps: receiving a material transfer instruction, the material transfer instruction carrying task list information; scanning the material identification of the current outgoing spare part to obtain material information; in the case that the material information matches the task list information, grabbing the spare part; determining the station identification corresponding to the task identification in the binding relationship of the task list information, and matching the target station coordinates corresponding to the material transfer instruction based on the station identification; generating a material transfer path according to the current position, the target station coordinates and the regional position relationship; transporting the spare part along the material transfer path, meanwhile, correcting the actual transportation track based on the anchor point information detected in the transportation process until the spare part is transported to the target station coordinates. The method can solve the problem of transfer deviation and improve the material transfer precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of transfer assembly of electrical control cabinet spare parts, and in particular relates to a body intelligent robot, a material transfer method, computer equipment, a computer readable storage medium and a computer program product. BACKGROUND

[0002] With the development of body intelligent technology, a technical scheme of using a robot to transfer materials appears in a production workshop. For example, in an electrical control cabinet production workshop, a robot can be used to take materials and transport them to corresponding electrical control cabinets. However, because there are many vertical libraries / stores in the production workshop, the environment is relatively complex, signal transmission is unstable, and the robot is prone to positioning and trajectory deviation problems caused by environmental interference during material transfer. Therefore, there is an urgent need for a scheme that can guarantee the material transfer accuracy of the robot. SUMMARY

[0003] Therefore, it is necessary to provide a body intelligent robot, a material transfer method, computer equipment, a computer readable storage medium and a computer program product capable of improving material transfer accuracy in view of the above technical problems.

[0004] In a first aspect, the present application provides a material transfer method applied to a body intelligent robot, and the method comprises the following steps.

[0005] Receiving a material transfer instruction, the material transfer instruction carrying task list information;

[0006] Scanning a material identifier of a current outgoing spare part to obtain material information;

[0007] In a case where the material information matches the task list information, grabbing the spare part;

[0008] Determining a workstation identifier corresponding to a task identifier in a binding relationship, and matching the target workstation coordinates corresponding to the material transfer instruction based on the workstation identifier;

[0009] Generating a material transfer path according to a current position, the target workstation coordinates and a regional position relationship;

[0010] Transporting the spare part along the material transfer path, and correcting an actual transportation trajectory based on anchor point information detected in the transportation process until the spare part is transported to the target workstation coordinates.

[0011] In one of the embodiments, the step of correcting the actual transportation trajectory based on the anchor point information detected in the transportation process comprises the following steps.

[0012] Collecting environmental information in the transportation process, identifying anchor point information in the environmental information;

[0013] Collecting inertial measurement data in the transportation process through an inertial measurement unit;

[0014] Fusing the anchor point information and the inertial measurement data to determine an actual transportation trajectory;

[0015] Correcting the actual transportation trajectory based on the material transfer path.

[0016] In one of the embodiments, the method further comprises:

[0017] In the case where the difference value between the material transfer path and the actual transportation trajectory is greater than a preset threshold value, stopping running and triggering a reset instruction.

[0018] In one of the embodiments, the generating of the material transfer path according to the current location, the target work station coordinates, and the regional location relationship comprises:

[0019] Determining a current transfer scenario based on the current location and the target work station coordinates;

[0020] Obtaining a regional location relationship corresponding to the current transfer scenario;

[0021] Taking the regional location relationship as a spatial constraint condition, performing collision-free planning on a route between the current location and the target work station coordinates to form the material transfer path.

[0022] In one of the embodiments, the grabbing of the spare part in the case where the material information and the task list information match comprises:

[0023] Collecting image information of the spare part, and determining a pose of the spare part according to the image information;

[0024] Adjusting a grabbing parameter of a mechanical arm based on the pose, and controlling the mechanical arm to perform a grabbing operation according to the grabbing parameter;

[0025] Collecting force feedback data of the mechanical arm in the process of approaching the spare part to perform the grabbing operation through a force sensor;

[0026] Secondarily calibrating the grabbing parameter according to the force feedback data, and controlling the mechanical arm to perform the grabbing operation according to the grabbing parameter after the secondary calibration;

[0027] In the process of performing the grabbing operation, adaptively adjusting a clamping force parameter of the mechanical arm based on force feedback data collected by the force sensor in real time.

[0028] In one of the embodiments, the method further comprises:

[0029] After the spare part is discharged, the spare part inventory information is updated.

[0030] In a second aspect, the application further provides a body-possessed intelligent robot, comprising a mobile chassis, a mechanical arm, a perception sensor, an end effector, and an industrial computer;

[0031] The mobile chassis, the mechanical arm, the perception sensor, the end effector, and the industrial computer are electrically connected in a loose coupling manner.

[0032] The industrial computer is configured to receive a material transfer instruction, the material transfer instruction carrying task sheet information; scan a material identifier of a currently discharged spare part through the perception sensor to obtain material information; control the mechanical arm and the end effector to grasp the spare part in a case where the material information matches the task sheet information; determine a work station identifier corresponding to a task identifier corresponding to the task sheet information, and match the target work station coordinates corresponding to the material transfer instruction based on the work station identifier; generate a material transfer path according to a current location, the target work station coordinates, and a regional positional relationship; and transport the spare part along the material transfer path through the mobile chassis, while correcting an actual transportation trajectory based on anchor point information detected by the perception sensor during transportation until the spare part is transported to the target work station coordinates.

[0033] In one of the embodiments, the industrial computer is further configured to control the mechanical arm and the end effector to perform an action corresponding to a teleoperation instruction sent by a teleoperation device in response to the teleoperation instruction, and collect and record sensor data when the action corresponding to the teleoperation instruction is performed through the perception sensor, train a body-possessed intelligent model based on the sensor data, and the body-possessed intelligent model is used to generate action logic parameters required by the body-possessed intelligent robot for working in an electrical control cabinet production scene.

[0034] In a third aspect, the application further provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the material transfer method of any one of the embodiments of the first aspect when executing the computer program.

[0035] In a fourth aspect, the application further provides a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the material transfer method of any one of the embodiments of the first aspect.

[0036] In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the material transfer method according to any one of the embodiments of the first aspect.

[0037] The above-mentioned embodied intelligent robot, material transfer method, computer device, computer readable storage medium and computer program product can receive a material transfer instruction, obtain material information by scanning a material identifier of a current outgoing spare part, in the case that the material information matches task sheet information of the material transfer instruction, grasp the spare part, determine a station identifier corresponding to a binding relationship of a task identifier of the task sheet information, match the target station coordinates corresponding to the material transfer instruction based on the station identifier, generate a material transfer path according to a current position, target station coordinates and a regional position relationship, transport the spare part along the material transfer path, and correct an actual transportation track based on anchor point information detected in the transportation process until the spare part is transported to the target station coordinates. Not only can the actual transportation track be corrected by using the anchor point information to improve the position accuracy of material transfer, but also the one-to-one correspondence of the instruction-material-station can be realized by using the matching of the material information and the task sheet information, the binding of the task identifier and the station identifier and the matching of the station identifier and the target station coordinates, and the operation accuracy of material transfer can be improved by ensuring the accuracy of the transfer process. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the description of the embodiments of the present application or the related art will be briefly introduced. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other related drawings can be obtained without creative labor on the basis of these drawings.

[0039] Figure 1 The application environment diagram of the material transfer method in an embodiment;

[0040] Figure 2 The flowchart of the material transfer method in an embodiment;

[0041] Figure 3 The flowchart of the actual transportation track correction step in an embodiment;

[0042] Figure 4 The flowchart of the material transfer path planning step in an embodiment;

[0043] Figure 5A The diagram of the regional position relationship corresponding to the workshop external transfer scene in an embodiment;

[0044] Figure 5BA schematic diagram of a region position relationship corresponding to a transfer scene in a workshop in an embodiment;

[0045] Figure 6 A flowchart of a spare part grabbing step in an embodiment;

[0046] Figure 7 A structural block diagram of the embodied intelligent robot 100 in an embodiment. DETAILED DESCRIPTION

[0047] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0048] It should be noted that the terms "first", "second", etc. used in the present application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "include" and "have" used in the present application and any variations thereof are intended to cover non-exclusive inclusion. The term "multiple" used in the present application refers to two or more. The term "and / or" used in the present application refers to one of the options or any combination of multiple options. The user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0049] The material transfer method provided by the embodiments of the present application can be applied to the application environment of an electrical control cabinet production workshop as shown in Figure 1 The electrical control cabinet production workshop includes a material center 11, a transfer station 13 and an assembly station 15.

[0050] The material center 11 mainly includes a vertical warehouse and a warehouse, which stores various types of spare parts required for electrical control cabinet assembly. The vertical warehouse can be used to store electronic components. The warehouse can be used to store auxiliary materials.

[0051] The transfer station 13 is mainly responsible for sorting, assembling, labeling, warehousing, statistics and other operations of electronic components, and directly supplies materials to the assembly station 15.

[0052] The assembly station 15 is mainly responsible for the assembly (such as rail, wire slot punching positioning, installation of various types of components, wiring, wiring and cover plate) and quality inspection of the electrical control cabinet, reports the surplus or default of materials in a preset period according to the use demand, and performs appearance quality inspection and component installation / continuity after assembly is completed.

[0053] The embodied intelligent robot 100 can be used to transport materials between the material center 11, the transfer station 13, and the assembly station 15.

[0054] In an exemplary embodiment, as shown, a material transfer method is provided, which is described below by taking the embodied intelligent robot 100 in the material center 11 as an example, including the following steps S202 to S212. Among them: Figure 2 Figure 1 Step S202, receiving a material transfer instruction, the material transfer instruction carrying task sheet information.

[0055] The task sheet information can be used to describe the material to be transferred, the task identification (such as task number) of the current transfer task, the creation time of the material transfer instruction, and the like.

[0056] Exemplarily, the embodied intelligent robot 100 can receive the material transfer instruction, and parse the material transfer instruction to obtain the task sheet information. Optionally, in some embodiments, after receiving the material transfer instruction, the embodied intelligent robot 100 can also automatically locate the current position, generate a motion trajectory from the current position to the material center 11, and go to the material center 11 to pick up the spare parts material.

[0057] Step S204, scanning the material identification of the current out-of-warehouse spare parts to obtain material information.

[0058] The material identification can include but is not limited to barcode, two-dimensional code, and the like.

[0059] The material information can include but is not limited to material name, material number, material size, and the like.

[0060] Exemplarily, before picking up the material, the embodied intelligent robot 100 can collect image information of the current out-of-warehouse spare parts through a visual sensor. The material identification of the spare parts in the image information is identified, and the material information of the spare parts is read by scanning the material identification. Optionally, in some embodiments, after entering the material center 11, the embodied intelligent robot 100 can also identify the material out-of-warehouse position through a preset target detection algorithm, and then go to the material out-of-warehouse position to collect the image information of the current out-of-warehouse spare parts.

[0061] Step S206, grabbing the spare parts in the case of matching the material information with the task sheet information.

[0062]

[0063] ​​Exemplarily, the embodied intelligent robot 100 can match the material information obtained through the current scanning with the task list information carried by the material transfer instruction in a string matching manner, or can extract corresponding field values from the material information and the task list information based on preset field names (such as a material number field) respectively, and match the field values corresponding to the same field name. In the case where it is determined that the material information of the current outgoing spare part matches the task list information carried by the material transfer instruction, it is determined that the current outgoing spare part is the material to be transferred this time. The spare part is grasped based on the position of the spare part.

[0064] In step S208, the station identifier corresponding to the task identifier in the task list information is determined, and the target station coordinates corresponding to the material transfer instruction are matched based on the station identifier.

[0065] Exemplarily, the embodied intelligent robot 100 can read the binding relationship between the identifiers from a preset database (for example, the database of the electrical control cabinet digital inventory management platform). Based on the binding relationship and the task identifier corresponding to the current task list information, the station identifier corresponding to the current task identifier is queried. Based on the station identifier, the station coordinates corresponding to the station identifier are matched from the preset database, as the target station coordinates corresponding to the material transfer instruction. It can be understood that the station identifier can include but is not limited to the transfer station identifier and the assembly station identifier. Accordingly, the target station coordinates can be in the area where the transfer station 13 is located or the area where the assembly station 15 is located.

[0066] In step S210, the material transfer path is generated according to the current position, the target station coordinates and the area position relationship.

[0067] The area position relationship can be used to describe the area position of the material center 11, the transfer station 13 and the assembly station 15 and the space division in the area (such as the hierarchical division of the vertical warehouse, the division of different types of spare part assembly areas, etc.).

[0068] Exemplarily, the embodied intelligent robot 100 can pre-store the area position relationship of the current electrical control cabinet production workshop, or can also scan the environment of the current electrical control cabinet production workshop through the positioning system carried by itself to obtain the area position relationship. Optionally, in some embodiments, the embodied intelligent robot 100 can divide the current environment into a plurality of grids based on the area position relationship, generate a collision-free material transfer path from the current position to the target work station coordinate based on the current position and the grid where the target work station coordinate is located. Alternatively, in some other embodiments, the embodied intelligent robot 100 can also utilize the area position relationship to perform dynamic scene three-dimensional modeling based on semantic segmentation on the current environment, perform obstacle avoidance planning on the path from the current position to the target work station coordinate based on the three-dimensional modeling data, and generate a corresponding material transfer path.

[0069] In step S212, the spare parts are transported along the material transfer path, and at the same time, the actual transportation trajectory is corrected based on the anchor point information detected in the transportation process until the spare parts are transported to the target work station coordinate.

[0070] The anchor point information can be used as a reference for the position of the embodied intelligent robot 100.

[0071] Exemplarily, the embodied intelligent robot 100 can send the material transfer path to the mobile chassis to instruct the mobile chassis to move along the material transfer path, while maintaining the grasping state of the spare parts by the robot arm. It can be understood that in the case that the embodied intelligent robot 100 has a storage space for placing the spare parts, the spare parts can also be placed in the storage space for transportation.

[0072] At the same time, in the process of transportation along the material transfer path, the embodied intelligent robot 100 can also collect anchor point information in the environment passed through in real time, correct the actual transportation trajectory according to the position difference between the anchor point information and the material transfer path, and move according to the corrected actual transportation trajectory. Until reaching the target work station coordinate to deliver the spare parts.

[0073] In the above material transfer method, by receiving the material transfer instruction, scanning the material identifier of the current outgoing spare part to obtain material information, in the case that the material information matches the task list information of the material transfer instruction, grabbing the spare part, determining the station identifier corresponding to the task identifier in the binding relationship, matching the target station coordinates corresponding to the material transfer instruction based on the station identifier, generating the material transfer path according to the current position, the target station coordinates and the regional position relationship, transporting the spare part along the material transfer path, and correcting the actual transportation trajectory based on the anchor point information detected in the transportation process until the spare part is transported to the target station coordinates, not only can the actual transportation trajectory be corrected by using the anchor point information to improve the position accuracy of the material transfer, but also the instruction-material-station one-to-one correspondence can be realized by using the matching of the material information and the task list information, the binding of the task identifier and the station identifier, and the matching of the station identifier and the target station coordinates, ensuring the accuracy of the transfer process, thereby improving the operation accuracy of the material transfer.

[0074] In one exemplary embodiment, as shown in Figure 3 Step S212 includes steps S302 to S308. Among them:

[0075] Step S302, collect the environmental information in the transportation process, and identify the anchor point information in the environmental information.

[0076] Among them, the anchor point information can come from the positioning identifier or laser reflection point arranged in the electrical control cabinet production workshop. The anchor point information can carry the position information of the positioning identifier or laser reflection point.

[0077] Exemplarily, in the process of transporting along the material transfer path, the embodied intelligent robot 100 can also collect environmental image information in real time through a visual sensor, identify the positioning identifier in the environmental image information to obtain the corresponding anchor point information. Or, the laser reflection point in the environment is detected in real time by using a laser sensor, and the corresponding anchor point information is determined based on the detection result of the laser reflection point.

[0078] Step S304, collect the inertial measurement data in the transportation process by the inertial measurement unit.

[0079] Among them, the inertial measurement data can include but not limited to attitude angle data, angular velocity data, acceleration data, etc.

[0080] Exemplarily, the embodied intelligent robot 100 can be equipped with an inertial measurement unit. In the process of transporting along the material transfer path, the embodied intelligent robot 100 can collect the inertial measurement data in the transportation process in real time through the inertial measurement unit.

[0081] Step S306, fuse the anchor point information and the inertial measurement data to determine the actual transportation trajectory.

[0082] Exemplarily, the embodied intelligent robot 100 can align the anchor point information and the inertial measurement data in the space-time dimension based on the timestamps corresponding to the anchor point information and the inertial measurement data. The fitted transport trajectory of the embodied intelligent robot 100 is fitted by using the aligned anchor point information. The deduced transport trajectory of the embodied intelligent robot 100 is deduced by using the aligned inertial measurement data. The contribution weights of the anchor point information and the inertial measurement data are adjusted according to the environmental light conditions, the metal density in the environment (metal structures are easy to cause multipath reflection, thereby affecting the reliability of the anchor point information of the laser reflection point), and the like. The fitted transport trajectory and the deduced transport trajectory are weighted and summed by using the corresponding contribution weights, so as to obtain the actual transport trajectory determined by fusing the anchor point information and the inertial measurement data.

[0083] In step S308, the actual transport trajectory is corrected based on the material transport path.

[0084] Exemplarily, the embodied intelligent robot 100 calculates the deviation between the actual transport trajectory and the material transport path. The motion parameters such as the motion direction, the angular velocity, and the acceleration are adjusted based on the deviation, so as to correct the actual transport trajectory to the direction of fitting the material transport path.

[0085] In this embodiment, by detecting the positioning marks or the laser reflection points in the current environment during the material transport process to obtain the anchor point information, and by weighting and fusing the trajectory fitted by the anchor point information and the trajectory deduced by the inertial sensor fusion positioning algorithm, a more accurate actual transport trajectory is obtained. The actual transport trajectory is corrected based on the material transport path in the ideal state, so as to improve the position accuracy of the material transport and the stability and safety of the running process.

[0086] In one exemplary embodiment, the material transport method provided in the present application can further include: in the case where the difference value between the material transport path and the actual transport trajectory is greater than a preset threshold value, stopping running and triggering a reset instruction.

[0087] Exemplarily, the embodied intelligent robot 100 can store a preset threshold value. The difference value between the material transport path and the actual transport trajectory is calculated. The difference value is compared with the preset threshold value. In the case where the difference value is greater than the preset threshold value, it indicates that the current positioning and navigation system fails, and the running needs to be stopped and the reset instruction is triggered. The reset instruction can restart the positioning and navigation system, and reposition the current position. Subsequently, the path planning can be regenerated based on the position repositioned after the reset instruction is executed and the material transport path.

[0088] In this embodiment, by automatically triggering stop and reset commands when there is abnormal deviation, the safety and positional accuracy of material transfer can be guaranteed.

[0089] In one exemplary embodiment, such as Figure 4 As shown, step S210 may include steps S402 to S406. Wherein:

[0090] Step S402: Determine the current transfer scenario based on the current location and the coordinates of the target workstation.

[0091] The transfer scenarios can include external transfer scenarios or internal transfer scenarios. External transfer scenarios can be used to characterize material transfers between material center 11 and transfer station 13. Internal transfer scenarios can be used to characterize material transfers between transfer station 13 and assembly station 15.

[0092] For example, the embodied intelligent robot 100 can determine whether the current transfer scenario belongs to the transfer scenario outside the workshop or the transfer scenario inside the workshop based on the area to which the current location belongs and the area to which the coordinates of the target workstation belong.

[0093] Step S404: Obtain the regional location relationship corresponding to the current transit scenario.

[0094] Step S406: Using the regional location relationship as a spatial constraint, perform collision-free route planning between the current location and the target workstation coordinates to form a material transfer path.

[0095] Optionally, in some implementations, if the current transfer scenario is determined to be an off-site transfer scenario, information such as... can be obtained. Figure 5A The diagram shows the spatial relationships of the areas corresponding to the off-site transfer scenario. The embodied intelligent robot 100 can... Figure 5A The spatial distribution of the neutral storage unit 51 serves as a spatial constraint for collision avoidance. A pre-defined path planning algorithm is used to calculate the route from the current location to the target workstation coordinates. The spatial constraints are then used to filter out routes that pass through the neutral storage unit 51. This results in material transfer paths that will not collide with the neutral storage unit 51.

[0096] In other implementations, when the current transfer scenario is determined to be an in-workshop transfer scenario, information such as... can be obtained. Figure 5B The diagram shows the spatial relationships of different areas within the workshop's transfer scenario. The embodied intelligent robot 100 can... Figure 5BThe positions of the workstations 53 and the electrical control cabinets 55 serve as the space constraint conditions for collision avoidance. Based on a preset path planning algorithm, a route between the current position and the target workstation coordinates is solved. The route passing through the workstations 53 and the electrical control cabinets 55 is filtered out by using the space constraint conditions. Thus, a material transfer path that does not collide with the workstations 53 and the electrical control cabinets 55 is obtained.

[0097] Alternatively, in other embodiments, if there are multiple routes that satisfy the space constraint conditions, the route with the shortest length or the largest distance between the points can be selected as the optimal material transfer path based on the route length, the distance between the points, and the like.

[0098] In this embodiment, by judging the current transfer scenario, the region position relationship corresponding to the current transfer scenario is obtained, the space constraint condition corresponding to the current transfer scenario is constructed, and the route between the current position and the target workstation coordinates is collision-free planned in combination with the space constraint condition to form the material transfer path. This can reduce the collision risk in the material transfer process and improve the safety of the material transfer.

[0099] In one exemplary embodiment, as shown in Figure 6 Step S206 can include the following steps S602 to S610. Among them:

[0100] Step S602, collect image information of the spare part, and determine the pose of the spare part according to the image information.

[0101] Step S604, adjust the grasping parameters of the mechanical arm based on the pose, and control the mechanical arm to perform grasping operation according to the grasping parameters.

[0102] Exemplarily, the embodied intelligent robot 100 can collect the image information of the spare part through the visual sensor. The image information is operated and processed to determine the position information and the attitude information of the current spare part as the pose of the spare part. The grasping parameters such as the grasping angle and the grasping attitude of the mechanical arm are adjusted based on the pose of the spare part. The position and the attitude of the mechanical arm are adjusted according to the grasping parameters, and the grasping operation is performed on the spare part by using the adjusted mechanical arm.

[0103] Step S606, collect force feedback data of the mechanical arm in the process of approaching the spare part to perform grasping operation through the force sensor.

[0104] Step S608, secondarily calibrate the grasping parameters according to the force feedback data, and control the mechanical arm to perform grasping operation according to the secondarily calibrated grasping parameters.

[0105] Exemplarily, the embodied intelligent robot 100 can be equipped with a force sensor. During the process of controlling the robot arm to approach the spare part to perform the grabbing operation, the force feedback data at the contact point between the robot arm and the spare part can be collected by the force sensor. According to the force feedback data, the grabbing parameters such as the grabbing angle and the grabbing posture of the robot arm are secondarily calibrated, and the robot arm is controlled to continue performing the grabbing operation according to the secondarily calibrated grabbing parameters.

[0106] In step S610, during the execution of the grabbing operation, the clamping force parameters of the robot arm are adaptively adjusted based on the force feedback data collected by the force sensor in real time.

[0107] Exemplarily, during the execution of the grabbing operation, the embodied intelligent robot 100 can continue to collect the force feedback data of the contact area between the robot arm and the spare part by the force sensor. The force feedback data is processed by combining a preset clamping force adaptive control algorithm (such as a proportional-integral-derivative (PID) adjustment algorithm, a Kalman filtering algorithm, an impedance model algorithm of “force-position” displacement, etc.), to generate an adaptive adjustment parameter. The clamping force parameters such as the clamping force intensity and the clamping force direction of the robot arm are adjusted by using the adaptive adjustment parameter, and the adjusted clamping force parameters are applied to perform the grabbing operation on the spare part.

[0108] Optionally, in some embodiments, a specific tooling can also be designed based on the shape of the spare part. The specific tooling is installed on the basis of the original structure of the robot arm to improve the stability of the robot arm in grabbing the spare part.

[0109] In this embodiment, by using visual recognition and force feedback to perform secondary calibration of the position and posture of the robot arm when grabbing the spare part, and combining the clamping force adaptive control algorithm to adjust the clamping force of the robot arm, the problems such as deviation and sliding of the spare part during the material transfer process can be prevented.

[0110] Optionally, in some embodiments, the above steps S602 to S610 can also be applied to the insertion and assembly scene of the spare part to prevent the problem of poor insertion and assembly.

[0111] In one exemplary embodiment, the material transfer method provided by the present application can further include: updating the spare part inventory information after the spare part is delivered out of the warehouse.

[0112] The spare part inventory information can include, but is not limited to, the inventory quantity of the spare part, the inventory model of the spare part, the material identification of the inventory spare part, and the like.

[0113] Exemplarily, a unified digital inventory management platform can be constructed based on the storage information of the spare parts in the warehouse and the storage. After the embodied intelligent robot 100 detects the spare parts out of the warehouse, the embodied intelligent robot 100 can send a spare part inventory update request to the digital inventory management platform to update the spare part inventory information stored in the digital inventory management platform.

[0114] In this embodiment, by updating the spare part inventory information in time after the spare parts are taken out, real-time synchronization of the inventory can be realized, and the problems of missing spare parts and repeated application of material transfer requests can be reduced.

[0115] Optionally, in some embodiments, the material transfer method provided in the present application can further include sorting the spare parts based on the material information. Exemplarily, when the embodied intelligent robot 100 transfers the spare parts to the transfer station 13 for the first time, the embodied intelligent robot 100 can also determine the category to which the spare parts belong according to the material information of the spare parts. Sorting the spare parts based on the category to which the spare parts belong and moving the spare parts to the storage area corresponding to the category can help improve the efficiency of subsequent transfer of the spare parts from the transfer station 13 to other areas.

[0116] It should be understood that, although each step in the flowchart involved in each of the above embodiments is displayed in sequence according to the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each of the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be alternately executed with at least part of other steps or steps or stages in other steps. It can be understood that the steps in different embodiments can be freely combined as needed, and various non-contradictory schemes formed by the combination are within the scope of protection of the present application.

[0117] Based on the same inventive concept, the embodiments of the present application also provide an embodied intelligent robot for implementing the above-mentioned material transfer method. The solution provided by the embodied intelligent robot is similar to the implementation scheme described in the above method, and therefore the specific limitations in one or more embodiments of the embodied intelligent robot provided below can refer to the limitations of the material transfer method described above, and will not be described here.

[0118] In one exemplary embodiment, as Figure 7As shown, a body-possessed intelligent robot 100 is provided, comprising a mobile chassis 702, a mechanical arm 704, a perception sensor 706, an end effector 708 and an industrial computer 710, wherein: the mobile chassis 702, the mechanical arm 704, the perception sensor 706, the end effector 708 and the industrial computer 710 are electrically connected in a loosely coupled manner. That is, based on the same inventive concept of the present application, those skilled in the art can delete or add other functional components according to actual use requirements. The body-possessed intelligent robot 100 provided by the present application has high deployment flexibility.

[0119] The industrial computer 710 can be used to receive a material transfer instruction carrying task sheet information. The material information is obtained by scanning the material identification of the current outgoing spare parts through the perception sensor 706. In the case that the material information matches the task sheet information, the mechanical arm 704 and the end effector 708 are controlled to grab the spare parts. The task identification corresponding to the task sheet information is determined to exist a binding relationship with the station identification, and the target station coordinates corresponding to the material transfer instruction are matched based on the station identification. According to the current location, the target station coordinates and the regional position relationship, the material transfer path is generated. The mobile chassis 702 transports the spare parts along the material transfer path, and at the same time, the actual transportation trajectory is corrected based on the anchor point information detected by the perception sensor 706 during transportation, until the spare parts are transported to the target station coordinates.

[0120] Optionally, in some embodiments, the industrial computer 710 can also be used to control the mechanical arm 704 and the end effector 708 to perform actions corresponding to the teleoperation instruction in response to the teleoperation instruction sent by the remote acquisition device, and collect and record the sensing data when the action corresponding to the teleoperation instruction is performed through the perception sensor 706, and train the body-possessed intelligent model based on the sensing data. The body-possessed intelligent model can be used to generate the action logic parameters required by the body-possessed intelligent robot 100 in the electrical control cabinet production scene. Wherein, the remote acquisition device can be used to represent a remote control device matched with the mechanical arm 704. The worker can send the teleoperation instruction to the industrial computer 710 by triggering the function button of the remote acquisition device, control the mechanical arm 704 and the end effector 708 to perform the action corresponding to the teleoperation instruction corresponding to the function button, for example, control the slave arm joint and the master arm joint of the mechanical arm 704 to calibrate, control the end effector 708 to open and close, etc. The action logic parameters can include but are not limited to the control logic parameters required by the automatic execution of the material taking action, the grabbing action, the sorting action, the assembly action, the labeling action, the rotating action, etc.

[0121] Optionally, in some embodiments, the perception sensor 706 can further include a head interaction device. The industrial computer 710 can be further configured to control the head interaction device to adjust its pitch angle and yaw angle in response to the teleoperation instruction for the head interaction device sent by the teleoperation device.

[0122] Optionally, in some embodiments, the industrial computer 710 can be further configured to control the mobile chassis 702 to move forward or backward or to move the yaw angle in response to the teleoperation instruction for the mobile chassis 702 sent by the teleoperation device.

[0123] Optionally, in some embodiments, the mobile chassis 702 can adopt a structure of double rear wheel differential drive plus front guide wheel to improve the steering flexibility and path stability of the body intelligent robot 100 during the material transfer process. In addition, the motor system of the mobile chassis 702 can be integrated with a reducer and a feedback sensor to realize smooth start and stop and precise motion control. The mobile chassis 702 can further be integrated with a positioning and navigation system to realize precise control of the steering motion.

[0124] Optionally, in some embodiments, the industrial computer 710 can be disposed above the mobile chassis 702. The industrial computer 710 can be integrated with an edge computing module to provide the data processing capability required for implementing the material transfer method in the above embodiments.

[0125] Optionally, in some embodiments, the perception sensor 706 can include but is not limited to force sensing sensors, vision and space perception sensors, attitude and motion state perception sensors, and interaction sensors.

[0126] Among them, the force sensing sensor can include a six-axis force / torque sensor for force perception, measuring three-dimensional orthogonal force, and realizing compliant control of the end effector 708. The force sensing sensor can be integrated in the end effector 708 and directly contact the load, such as the spare parts transferred in the above embodiments.

[0127] The visual and spatial perception sensors can be integrated above the mobile chassis 702 by the lifting device. The visual and spatial perception sensors can include, but are not limited to, visual / depth camera modules, laser radars, proximity sensors, etc. The visual / depth camera modules can be used to combine color RGB images with depth information to achieve environment perception and obstacle avoidance, and the data acquisition range covers the direction of travel of the embodied intelligent robot 100. The visual / depth camera modules can be installed in a lateral manner to eliminate the lateral blind area. The laser radar can be used to construct a high-precision environment map by scanning point clouds. The laser radar can be integrated on the top of the embodied intelligent robot 100 to avoid being blocked by the vehicle body. At the same time, the bottom of the laser radar can be installed in a tilted manner to detect low obstacles in the environment. The proximity sensor can be used to measure the approach speed of obstacles in the environment.

[0128] The attitude and motion state perception sensors can include, but are not limited to, inertial measurement sensors. The inertial measurement sensors can be used to achieve attitude feedback and control. The inertial measurement sensors can be integrated in the center of the mobile chassis 702 to reduce vibration interference.

[0129] The interaction sensors can include, but are not limited to, microphone arrays / auditory sensors / sounds, tactile sensors, etc. The microphone array / auditory sensor / sound can be used to achieve natural human-computer voice interaction. The tactile sensor can be integrated on the contact area of the end effector 708 (such as the jaw or the surface of the suction cup).

[0130] Optionally, in some embodiments, the end effector 708 can adopt a universal connection flange design and be installed at the end of the mechanical arm 704.

[0131] The above-mentioned various modules in the embodied intelligent robot 100 can be implemented by software, hardware, and combinations thereof, in whole or in part. The above-mentioned various modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the above-mentioned various modules.

[0132] Those skilled in the art can understand that the structure shown in the above description and drawings is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0133] In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps in the above-mentioned various method embodiments.

[0134] In an exemplary embodiment, a computer readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, implements the steps of any of the above method embodiments.

[0135] In an exemplary embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of any of the above method embodiments.

[0136] A person of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium and can include the processes of the above method embodiments when executed. Any reference to a memory, database or other medium in the embodiments provided by the present application can include at least one of a non-volatile memory and a volatile memory. The non-volatile memory can include a read-only memory (ROM), a magnetic tape, a floppy disk, a flash memory, an optical storage, a high-density embedded non-volatile memory, a resistive random access memory (ReRAM), a magnetoresistive random access memory (MRAM), a ferroelectric random access memory (FRAM), a phase change memory (PCM), a graphene memory, etc. The volatile memory can include a random access memory (RAM) or an external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms such as a static random access memory (SRAM) or a dynamic random access memory (DRAM), etc. The database involved in the embodiments provided by the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided by the present application can be a general processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0137] Any technical features in the above embodiments can be combined, and for the sake of brevity, not all possible combinations are described above, however, any combination of these technical features is deemed to be within the scope of the present application.

[0138] The above embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the patent scope of the present application. It should be pointed out that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A material transfer method, characterized in that, Applied to embodied intelligent robots, the method includes: Receive a material transfer instruction, which carries task order information; Scan the material identifier of the currently outbound spare parts to obtain material information; If the material information matches the task order information, the spare parts will be retrieved. Determine the workstation identifier that is bound to the task identifier corresponding to the task order information, and obtain the target workstation coordinates corresponding to the material transfer instruction based on the workstation identifier; Based on the current location, the coordinates of the target workstation, and the regional location relationship, a material transfer path is generated; The spare parts are transported along the material transfer path. At the same time, the actual transportation trajectory is corrected based on the anchor point information detected during transportation until the spare parts are transported to the target workstation coordinates. The method of correcting the actual transportation trajectory based on anchor point information detected during transportation includes: Collect environmental information during the transportation process, identify anchor point information in the environmental information, the anchor point information comes from positioning markers or laser reflection points deployed in the electrical control cabinet production workshop, and the anchor point information carries the location information of the positioning markers or laser reflection points; Inertial measurement data during the transportation process is collected using an inertial measurement unit; Determining the actual transportation trajectory by integrating the anchor point information and the inertial measurement data includes: aligning the anchor point information and the inertial measurement data in the spatiotemporal dimension based on the timestamps corresponding to the anchor point information and the inertial measurement data; fitting a fitted transportation trajectory using the aligned anchor point information; performing calculations on the aligned inertial measurement data to obtain the derived transportation trajectory; adjusting the contribution weights of the anchor point information and the inertial measurement data according to ambient lighting conditions and the metal density in the environment; and performing weighted calculations on the fitted transportation trajectory and the derived transportation trajectory using the corresponding contribution weights and summing them to obtain the actual transportation trajectory. The actual transportation trajectory is corrected based on the material transfer path.

2. The method according to claim 1, characterized in that, The method further includes: If the difference between the material transfer path and the actual transportation trajectory exceeds a preset threshold, the operation will stop and a reset command will be triggered.

3. The method according to claim 1, characterized in that, The step of generating a material transfer path based on the current location, the coordinates of the target workstation, and the regional location relationship includes: Based on the current location and the coordinates of the target workstation, the current transfer scenario is determined; Obtain the regional location relationship corresponding to the current transfer scenario; Using the regional location relationship as a spatial constraint, a collision-free route is planned between the current location and the target workstation coordinates to form the material transfer path.

4. The method according to claim 1, characterized in that, When the material information matches the task order information, retrieving the spare parts includes: The image information of the component is acquired, and the pose of the component is determined based on the image information; Based on the posture adjustment of the robotic arm's grasping parameters, the robotic arm is controlled to perform grasping operations according to the grasping parameters; Force feedback data is collected by the force sensor as the robotic arm performs a grasping operation near the part. The grasping parameters are calibrated a second time based on the force feedback data, and the robotic arm is controlled to perform the grasping operation according to the grasping parameters after the second calibration. During the grasping operation, the clamping force parameters of the robotic arm are adaptively adjusted based on the force feedback data collected in real time by the force sensor.

5. The method according to claim 1, characterized in that, The method further includes: After the spare parts are shipped out, update the spare parts inventory information.

6. A embodied intelligent robot, characterized in that, This includes a mobile chassis, robotic arm, sensing sensors, end effector, and industrial computer; The mobile chassis, the robotic arm, the sensing sensor, the end effector, and the industrial computer are electrically connected in a loosely coupled manner. The industrial control computer receives material transfer instructions, which carry task order information. It scans the material identifiers of currently outgoing parts using the sensing sensors to obtain material information. If the material information matches the task order information, it controls the robotic arm and the end effector to grasp the parts. It identifies workstation identifiers that are bound to the task identifiers corresponding to the task order information, and obtains the target workstation coordinates corresponding to the material transfer instruction based on these workstation identifiers. It generates a material transfer path based on the current location, the target workstation coordinates, and the regional location relationship. The mobile chassis transports the parts along the material transfer path, and simultaneously corrects the actual transport trajectory based on anchor point information detected by the sensing sensors during transport, until the parts are transported to the target workstation coordinates. The step of correcting the actual transportation trajectory based on the anchor point information detected by the sensing sensors during transportation includes: Collect environmental information during the transportation process, identify anchor point information in the environmental information, the anchor point information comes from positioning markers or laser reflection points deployed in the electrical control cabinet production workshop, and the anchor point information carries the location information of the positioning markers or laser reflection points; Inertial measurement data during the transportation process is collected using an inertial measurement unit; Determining the actual transportation trajectory by integrating the anchor point information and the inertial measurement data includes: aligning the anchor point information and the inertial measurement data in the spatiotemporal dimension based on the timestamps corresponding to the anchor point information and the inertial measurement data; fitting a fitted transportation trajectory using the aligned anchor point information; performing calculations on the aligned inertial measurement data to obtain the derived transportation trajectory; adjusting the contribution weights of the anchor point information and the inertial measurement data according to ambient lighting conditions and the metal density in the environment; and performing weighted calculations on the fitted transportation trajectory and the derived transportation trajectory using the corresponding contribution weights and summing them to obtain the actual transportation trajectory. The actual transportation trajectory is corrected based on the material transfer path.

7. The embodied intelligent robot according to claim 6, characterized in that, The industrial control computer is also used to respond to remote operation commands sent by the remote acquisition device, control the robotic arm and the end effector to perform actions corresponding to the remote operation commands, and collect and record sensing data when performing actions corresponding to the remote operation commands through the sensing sensors. Based on the sensing data, an embodied intelligent model is trained. The embodied intelligent model is used to generate the motion logic parameters required for the embodied intelligent robot to operate in the electrical control cabinet production scenario.

8. The embodied intelligent robot according to claim 6, characterized in that, The industrial control computer is also used to stop running and trigger a reset command when the difference between the material transfer path and the actual transportation trajectory is greater than a preset threshold.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

Images