CN115256464A - Detection method and device for robot capsule, robot and related product - Google Patents
Detection method and device for robot capsule, robot and related product Download PDFInfo
- Publication number
- CN115256464A CN115256464A CN202210890010.1A CN202210890010A CN115256464A CN 115256464 A CN115256464 A CN 115256464A CN 202210890010 A CN202210890010 A CN 202210890010A CN 115256464 A CN115256464 A CN 115256464A
- Authority
- CN
- China
- Prior art keywords
- door
- capsule
- robot
- pod
- detection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/0095—Means or methods for testing manipulators
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Manipulator (AREA)
Abstract
The invention provides a detection method and a detection device for a robot capsule, a robot and a related product, wherein the method comprises the following steps: acquiring standard data of the capsule; detecting actual data of the capsule; comparing the standard data with the actual data to obtain a difference result of the actual data and the standard data; and analyzing a difference reason according to the difference result, and outputting a correction suggestion based on the difference reason. The invention can avoid the problems of too many alarms and difficult detection recurrence caused by single detection parameters, incapability of process detection and assembly condition detection, is beneficial to a user to position a fault position and a fault reason in time and correct in time, avoids the problems of errors in manual inspection and more time consumption for fault communication, and improves the detection efficiency.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of robots, in particular to a method and a device for detecting a cabin box of a robot, the robot and a related product.
[ background of the invention ]
Generally, a capsule is arranged in the service robot, the capsule is used for accommodating articles such as take-out articles and express delivery articles, and a capsule door of the capsule needs to be opened or closed to enable a user to take and place the articles in the capsule. In the existing detection for the functions of the cabin box, only the detection of whether the cabin door is successfully opened or closed through time delay is included, whether the cabin door is actually in place or not and the opening and closing process of the cabin door cannot be detected, so that excessive alarming can be caused, the detected parameters are single, the fault position and the fault reason cannot be quickly positioned, the detection and recurrence are difficult, the manpower waste is caused, the communication time is long, and the operation requirement cannot be met.
In view of the above, it is desirable to provide a novel method and apparatus for detecting a robot pod, a robot, and a related product to overcome the above-mentioned drawbacks.
[ summary of the invention ]
The invention aims to provide a detection method and device for a robot capsule, a robot and related products, which can avoid the problems of too many alarms and difficult detection recurrence caused by single detection parameters, incapability of process detection and assembly condition detection.
In order to achieve the above object, in a first aspect, the present invention provides a method for detecting a robot pod, including the steps of: acquiring standard data of the capsule; detecting actual data of the capsule; comparing the standard data with the actual data to obtain a difference result of the actual data and the standard data; and analyzing a difference reason according to the difference result, and outputting a correction suggestion based on the difference reason.
In a preferred embodiment, the standard data comprises one or more of door speed, door acceleration, motor speed, motor acceleration, motor torque, motor current, door gap, door panel gap, door shaft radius of rotation, position of door screw bearings on and off, position of stickers, distance of sliding rails, and height difference of sliding rails.
In a preferred embodiment, the step of detecting the actual data of the capsule comprises: detecting the instantaneous speed of the hatch of the capsule during opening or closing; calculating an acceleration of the door during opening or closing based on the instantaneous velocity.
In a preferred embodiment, the step of calculating the acceleration of the door during opening or closing based on the instantaneous velocity further comprises: calculating the moment of the cabin door in the opening or closing process according to the acceleration; and calculating the current of the motor by combining the moment and the inherent parameters of the motor driving the hatch door to open or close.
In a preferred embodiment, the step of detecting the actual data of the capsule comprises: shooting a door opening picture or a door closing picture through a camera after the cabin door is opened or closed; and acquiring the door opening clearance or the door closing clearance of the capsule based on the door opening picture or the door closing picture.
In a preferred embodiment, the step of detecting the actual data of the capsule comprises: shooting an appearance picture of the capsule through a camera; and acquiring the door plate clearance, the door shaft rotating radius and the door opening and closing screw bearing position of the cabin box based on the appearance picture.
In a preferred embodiment, after the step of taking the picture of the appearance of the capsule by the camera, the method further comprises: and acquiring the sticker position of the capsule based on the appearance picture.
In a preferred embodiment, after the step of taking the picture of the appearance of the capsule by the camera, the method further comprises: acquiring the sliding rail distance and the sliding rail height difference of the capsule based on the appearance picture; and calculating the parallelism of the sliding rails by combining the distance between the sliding rails and the height difference of the sliding rails.
In a second aspect, the present invention provides a detection apparatus for a robot pod, comprising: the acquisition module is used for acquiring standard data of the capsule; the detection module is used for detecting actual data of the capsule; the comparison module is used for comparing the standard data with the actual data and obtaining a difference result of the actual data and the standard data; and the analysis module is used for analyzing a difference reason according to the difference result and outputting a correction suggestion based on the difference reason.
When the detection device for the robot capsule provided by the second aspect of the present invention is implemented, the capsule detection of the robot can be implemented by using the detection method for the robot capsule described in any embodiment of the first aspect of the present invention.
In a third aspect, the present invention also provides a robot comprising: a memory and one or more processors; the memory for storing one or more computer programs; the one or more computer programs, when executed by the one or more processors, implement the method for detection of a robot pod of any of the embodiments of the first aspect of the present invention.
In a fourth aspect, the present invention further provides a computer storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the method for detecting a robot pod is implemented according to any one of the embodiments of the first aspect of the present invention.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program or instructions which, when executed by a processor, implements the method for detecting a robot pod of any of the embodiments of the first aspect of the present invention.
Compared with the prior art, the detection method, the detection device, the robot and the related products of the robot capsule provided by the invention can acquire the standard data of the capsule, detect the actual data of the capsule, compare the standard data with the actual data to obtain the difference result of the actual data and the standard data, analyze the difference reason according to the difference result, and output the correction suggestion based on the difference reason, so that the problems of too many alarms and difficulty in detection recurrence caused by single detection parameters, incapability of performing process detection and assembly condition detection can be avoided, a user can timely position a fault position and a fault reason and timely correct the fault position and the fault reason, the problems of errors in manual inspection, more time consumption in fault communication and the like are avoided, and the detection efficiency is improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic block diagram of a detection device of a robot pod provided by the present invention;
FIG. 2 is a flow chart of a method of inspection of a robotic pod provided in the present invention;
fig. 3 is a schematic block diagram of a robot provided by the present invention.
[ detailed description ] embodiments
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Please refer to fig. 1, which is a schematic block diagram of a detection apparatus for a robot pod according to the present invention. The detection device 100 for the robot capsule provided by the invention comprises an acquisition module 10, a detection module 20, a comparison module 30 and an analysis module 40.
Specifically, the obtaining module 10 is configured to obtain standard data of the pod; the detection module 20 is used for detecting the actual data of the capsule; the comparison module 30 is used for comparing the standard data with the actual data and obtaining a difference result between the actual data and the standard data; the analysis module 40 is configured to analyze a difference reason according to the difference result, and output a modification suggestion based on the difference reason.
Further, the standard data comprises one or more of cabin door speed, cabin door acceleration, motor speed, motor acceleration, motor torque, motor current, cabin door clearance, door plate clearance, door shaft rotation radius, door opening and closing screw bearing position, sticker position, slide rail distance and slide rail height difference. In later implementation, the standard data can be increased according to needs, and the method in the application is also applicable.
Further, the detection module 20 includes a speed detection unit and an acceleration calculation unit. The speed detection unit is used for detecting the instantaneous speed of the cabin door of the cabin box in the opening or closing process; the acceleration calculating unit is used for calculating the acceleration of the cabin door during the opening or closing process based on the instantaneous speed.
The detection module 20 further includes a torque calculation unit and a current calculation unit. The moment calculation unit is used for calculating the moment of the cabin door in the opening or closing process according to the acceleration; and the current calculation unit is used for calculating the current of the motor when the cabin door is opened or closed by combining the torque and the inherent parameters of the motor driving the cabin door to be opened or closed.
Further, the detection module 20 includes a first shooting unit and a first obtaining unit. The first shooting unit is used for shooting a door opening picture or a door closing picture through a camera after the cabin door is opened or closed; the first acquisition unit is used for acquiring the door opening clearance or the door closing clearance of the capsule based on the door opening picture or the door closing picture.
Further, the detection module 20 further includes a second shooting unit and a second obtaining unit. The second shooting unit is used for shooting an appearance picture of the capsule through a camera; and the second acquisition unit is used for acquiring the door plate clearance, the door shaft rotating radius and the door opening and closing screw bearing position of the capsule based on the appearance picture.
The detection module 20 further includes a third obtaining unit, which is configured to obtain a sticker position of the pod based on the appearance picture.
In a preferred embodiment, the detection module 20 further includes a fourth obtaining unit and a parallelism calculating unit. The fourth acquisition unit is used for acquiring the sliding rail distance and the sliding rail height difference of the capsule based on the appearance picture; and the parallelism calculating unit is used for calculating the parallelism of the slide rails by combining the slide rail distance and the slide rail height difference.
It will be appreciated that the various functional modules and units described above may be stored in the form of software programs in memory and executed by the processor. In an alternative embodiment, each of the functional modules and units may also be a hardware with a specific function, for example, a chip burned with a specific software program.
When the detection device of the robot capsule is implemented, the steps of any one of the detection methods of the robot capsule shown in fig. 2 can be implemented, or the detection method of the robot capsule is adopted to implement the detection of the robot capsule.
The functional modules and units are described in detail below with reference to fig. 2.
As shown in fig. 2, it is a flowchart of a detection method of a robot pod provided by the present invention. It should be noted that the method of the present invention is not limited to the order of the following steps, and in other embodiments, the method of the present invention may include only a portion of the following steps, or some of the steps may be deleted. In implementation, the detection method of the robot capsule can be realized by the detection device of the robot capsule, and the detection device can realize detection of the robot capsule by adopting the detection method described in this embodiment.
The invention provides a detection method of a robot capsule, which comprises the following steps:
step S10: standard data of the capsule are acquired. Specifically, a standard data model may be constructed, the standard data includes, for example, a cabin door speed, a cabin door acceleration, a motor speed, a motor acceleration, a motor torque, a motor current, a cabin door gap, a door panel gap, and the like, the standard data is preset data of a cabin box design, and the acquisition module 10 may acquire the standard data of the cabin box.
Step S20: detecting actual data of the capsule. Specifically, the detection module 20 can detect actual data of the pod, specifically can acquire the actual data through a sensor and/or an actuator, and can perform data frame analysis, measurement and calculation, for example, detect the instantaneous speed of the pod door of the pod in the opening or closing process through a speed sensor to realize the detection of the door opening and closing process, or acquire the door plate gap, the door shaft rotation radius, the door opening and closing screw bearing position and the like of the pod through an appearance picture shot by a camera to realize the detection of the door plate assembly condition, finally realize the detection of the operation process and the assembly condition, and the like, thereby avoiding the problems of excessive alarm and single detection parameter.
In particular, multiple cameras may be mounted at multiple locations of the pod to obtain pictures at the multiple locations. For example, a camera is installed near a door panel to obtain an appearance picture including the whole door panel (or including surrounding parts of the door panel at the same time), then picture frame analysis and measurement are performed, data such as the edge of the door panel in the picture are identified, a gap between the door panel in the picture is obtained, an actual door panel gap is calculated by combining parameters such as the actual distance between the camera and the door panel and the gap between the door panel in the picture, and finally actual data of the capsule is obtained. It can be understood that other parameters such as the rotation radius of the door shaft and the position of the screw bearing for opening and closing the door can be obtained by acquiring pictures through the camera and performing picture frame analysis and measurement, and are not described in detail herein.
Of course, the camera may be mounted on the robot body and may be capable of acquiring corresponding image data as a standard, or may be mounted on other devices to use related image data on the robot body.
Step S30: and comparing the standard data with the actual data to obtain a difference result of the actual data and the standard data. Specifically, the comparison module 30 can compare the standard data with the actual data to obtain a difference result between the actual data and the standard data, compare the actual data with the standard data model to calculate a deviation, and output a difference result, where the difference result may be a size difference result or a dynamic difference curve.
Step S40: and analyzing a difference reason according to the difference result, and outputting a correction suggestion based on the difference reason. Specifically, the robot may be pre-stored with difference reasons and correction suggestions corresponding to data differences, and after a difference result between actual data and standard data is obtained, the analysis module 40 may analyze the difference reasons according to the difference result and output the correction suggestions based on the difference reasons, and the difference reasons and the correction suggestions may be displayed on a display screen of the robot in the form of characters, pictures, videos, and the like, so as to facilitate a user to locate a fault position and a fault reason in time and correct the fault position and the fault reason in time, and the detection efficiency is high.
Therefore, the detection method of the robot capsule provided by the invention can acquire the standard data of the capsule, detect the actual data of the capsule, compare the standard data with the actual data to obtain the difference result of the actual data and the standard data, analyze the difference reason according to the difference result, and output the correction suggestion based on the difference reason, can avoid the problems of too many alarms and difficult detection recurrence caused by single detection parameter, incapability of process detection and assembly condition detection, is beneficial to a user to timely position a fault position and a fault reason, timely correct the fault position and the fault reason, avoids the problems of errors in manual detection and more time consumption in fault communication, and improves the detection efficiency.
In this embodiment, the standard data includes one or more of a cabin door speed, a cabin door acceleration, a motor torque, a motor current, a cabin door gap, a door panel gap, a door shaft rotation radius, a door opening and closing screw bearing position, a sticker position, a slide rail distance, and a slide rail height difference. In other embodiments, the standard data may also include one or more of pod clearance (i.e., clearance of the pod from the robot body), motor speed, motor acceleration, and the like.
Further, step S20 includes the steps of:
detecting the instantaneous speed of the hatch of the capsule during opening or closing;
calculating an acceleration of the door during opening or closing based on the instantaneous velocity.
Specifically, the detection method can detect whether the door opening and closing state of the cabin box is normal, for example, dynamic speed measurement is performed in the opening or closing process of the cabin door, the instantaneous speed at the position of the cabin door is calculated in real time and converted into acceleration, so as to judge whether the door opening state or the door closing state is normal, and whether the door opening state or the door closing state has dynamic state information of door opening and closing, such as rebound, jitter, jamming, not-in-place opening, not-in-place closing and the like. It can be understood that the speed is judged to be greater than 0 according to the direction, the door is opened and closed, the acceleration is judged to be normal according to the speed control relation after conversion is finished and according to expectation, and is judged to be a state fault if not according to the expectation, and an alarm is given, so that a user can conveniently process the fault in time. Whether the difference result is in accordance with the expectation is judged by comparing the actual data with the standard data, if the difference result is in the allowable range, namely the allowable error range, the difference result is judged to be in accordance with the expectation, and if the difference result is beyond the allowable range, the difference result is judged to be not in accordance with the expectation.
In the embodiment, the cabin box is connected with a monitoring mainboard for realizing data calculation, storage, uploading, fault alarm and the like. The cabin box comprises four box plates, and the box plates are used for realizing speed calculation and feedback, position judgment and feedback, current measurement and feedback, in-place detection and feedback, speed control and feedback, steering engine control and feedback, cabin box weight measurement and feedback, light curtain component signal receiving and feedback and the like. Specifically, the number of the light curtains is four, the light curtains are used for measuring the door opening position, and the precision level is 0.01MM.
Further, after the step of calculating the acceleration of the door during opening or closing based on the instantaneous velocity, the method further includes:
calculating the moment of the cabin door in the opening or closing process according to the acceleration;
and calculating the current of the motor by combining the moment and the inherent parameters of the motor driving the hatch door to open or close.
Specifically, the moment can be calculated through the acceleration, the information such as the current of the door opening motor can be calculated by combining the characteristics of the motor, and whether the motor is abnormal or not and whether the motor is stuck or not can be judged; calculating the current of the motor by means of the torque and the motor parameters can be accomplished by using known techniques. The cabin door opening and closing device has the advantages that the current of the motor drives the cabin door to open and close according to a certain speed and acceleration, whether the current value and the current fluctuation are within an allowable range can be judged, if the current value and the current fluctuation are within the allowable range, the state is judged to be normal, if the current value and the current fluctuation are within the range, the state is judged to be abnormal, and if the current value and the current fluctuation exceed the range, the state is uploaded for alarming.
In the embodiment, the number of the motors is four, the motors are provided with encoders, the motion angle of the door panel of the cabin door can be sensed, the precision level is 2000, the motor torque force measuring function is realized, the force of 0.5-300N can be measured, and the precision level is 0.5N.
Further, step S20 further includes the steps of:
shooting a door opening picture or a door closing picture through a camera after the cabin door is opened or closed;
and acquiring the door opening clearance or the door closing clearance of the capsule based on the door opening picture or the door closing picture.
Specifically, the static state information of the opening and closing door such as the situation that the cabin door is not opened in place and closed in place can be judged through the static state of the cabin door, for example, the gap is checked through a camera, the state is judged to be normal if the gap is in accordance with the expectation in the range, the state is judged to be abnormal if the gap exceeds the range, and the alarm is uploaded.
In the present embodiment, step S20 includes the steps of:
shooting an appearance picture of the capsule through a camera;
and acquiring the door plate clearance, the door shaft rotating radius and the door opening and closing screw bearing position of the cabin box based on the appearance picture.
Specifically, the appearance pictures of a plurality of positions of the capsule can be respectively shot through a plurality of cameras so as to detect the assembly condition of the components. For example, static detection of door panel gap, identification of door panel edge, calculation of door panel gap, parallelism and the like are used for failure analysis, the gap is checked through a camera, if the gap is in accordance with expectations in a range, the state is judged to be normal, if the gap exceeds the range, the state is judged to be abnormal, and the alarm is uploaded. The central position of the door shaft is measured and calculated through static analysis to judge whether the incoming material is normal or not, the rotating radius of the door shaft is checked through a camera, the door shaft is judged to be normal if the door shaft is in accordance with expectations within a range, the door shaft is judged to be abnormal if the door shaft exceeds the range, and the door shaft is uploaded to alarm. Whether the installation of a screw bearing for opening and closing a door is normal is detected, namely, the position of the screw bearing is statically detected, whether the screw thread of the screw bearing is loosened is judged, the distance between the end of the screw bearing and the top of the sliding chute is calculated for failure analysis, the gap of the screw bearing is checked through a camera, the gap is in accordance with the expectation in the range and is judged to be normal, the gap exceeds the range and is judged to be abnormal, and the door is uploaded to give an alarm. By the design, the assembly condition detection of the cabin box parts can be realized, and the timely elimination of assembly faults is facilitated.
In some embodiments, the number of the cameras is four, the accuracy level is 0.01MM, the cameras are used for shooting door opening pictures, door closing pictures, appearance pictures and the like, and the cameras can be used for shooting the position of the installed cabin door, judging the deviation distance of the installation position of the cabin door, determining the installation accuracy of the static cabin door, judging the door opening shaking action, judging the door opening rebounding action, judging the secondary door opening action, judging the state of the door opening position, judging the door closing position action, judging the door opening repeatedly, judging the door closing repeatedly and the like.
Further, after the step of taking the picture of the appearance of the pod by the camera, the method further comprises:
and acquiring the sticker position of the capsule based on the appearance picture.
Specifically, whether the pasting position of the sticker is normal or not and whether the switch of the cabin door is influenced or not are calculated through static measurement and analysis, the edge gap is checked through the camera, the gap is in accordance with the expectation in the range, the state is judged to be normal, the gap exceeding the range is judged to be abnormal, and uploading is carried out for alarming. Whether the position is normally pasted to static measurement analysis calculation sticker, whether influence the screw rod bearing operation, through camera inspection edge clearance, the clearance accords with the expectation then judges as the state normal in the within range, surpasss the scope and judges as the state unusual, uploads the warning.
In this embodiment, after the step of taking the picture of the appearance of the pod by the camera, the method further includes:
acquiring the sliding rail distance and the sliding rail height difference of the capsule based on the appearance picture;
and calculating the parallelism of the sliding rails by combining the distance between the sliding rails and the height difference of the sliding rails.
Specifically, four sliding rails are usually installed below the cabin box and used for installing a steering engine to automatically unlock and lock the cabin box, and functions of weighing, bearing a door opening motor, installing a box body plate and the like can be realized. The state of the slide rails can be statically detected to judge whether the parallelism between the slide rails meets the standard or not, judge and calculate the relative distance of the slide rails, check the distance and the height difference of the slide rails through the camera, calculate the parallelism according to the distance and the height difference, judge that the state is normal if the parallelism meets the expectation in the range, judge that the state is abnormal if the parallelism exceeds the range, and upload and alarm.
In other embodiments, a gap between the pod and the robot body may be further acquired based on the appearance picture to detect whether the pod assembly meets a functional requirement. For example, the relative position of the capsule in the robot is statically detected to judge whether the capsule can be normally used or not, the camera is used for checking the gap between the capsule and the robot, if the gap is in accordance with the expectation in the range, the state is judged to be normal, if the gap exceeds the range, the state is judged to be abnormal, and the alarm is uploaded.
The detection method of the robot capsule provided by the invention can acquire pictures and videos through the camera, perform picture frame analysis and measurement, acquire the sizes of gaps, gaps and intervals, calculate the deviation by comparing with a standard data model, mark the deviation size, draw a deviation data analysis table, acquire the door opening and closing speed and current values through the motor, perform numerical analysis and calculation, acquire the speed and acceleration, calculate the deviation by comparing with the standard data model, draw the deviation data analysis table, perform physical inspection and analysis through the difference result, judge and correct the cause of the problem, find the deviation, the deviation size, the fault picture and the video in the assembly process through inspection, solve the problems that the alarm is too much and the inspection is difficult to reappear due to the fact that only time delay detection is carried out, actual in-place detection and process detection are not carried out, avoid the problems that the error exists in manual inspection and the communication consumes more time, facilitate the later-stage fault backtracking, and reduce the disorder and loss of artificial information transmission.
Referring to fig. 3, the present invention further provides a robot, including: a memory 210 and one or more processors 220.
In particular, memory 210 is used to store one or more computer programs; the one or more computer programs, when executed by the one or more processors 220, implement the method for detecting a robot pod of any of the embodiments described above.
The Memory 210 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 210 is configured to store a program, and the processor 220 runs the program after receiving the execution instruction, so as to implement the detection method for the robot pod according to the another embodiment. It will be appreciated that access to the memory 210 by the processor 220, and possibly other components, may be under the control of a memory controller.
The processor 220 may be an integrated circuit chip having signal processing capabilities. The Processor 220 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like, and may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods and steps disclosed in any embodiment of the present invention.
The invention further provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and when the computer program is executed by a processor, the detection method of the robot capsule in any one of the embodiments is realized.
The invention also provides a computer program product comprising a computer program or instructions which, when executed by a processor, implement the method for detecting a robot pod as described in any of the preceding embodiments.
It should be noted that all the embodiments of the method for detecting a robot pod according to the present invention are applicable to the apparatus 100 for detecting a robot pod, the robot, the computer storage medium, and the computer program product according to the present invention, and all the embodiments can achieve the same or similar beneficial effects.
In summary, the detection method, the detection device, the robot, the computer storage medium and the computer program product for the robot capsule provided by the invention can acquire the standard data of the capsule, detect the actual data of the capsule, compare the standard data with the actual data to obtain the difference result between the actual data and the standard data, analyze the difference reason according to the difference result, and output the correction suggestion based on the difference reason, so that the problems of too many alarms and difficult detection recurrence caused by single detection parameters, incapability of process detection and assembly condition detection can be avoided, the user can position the fault position and the fault reason in time and correct the fault position and the fault reason in time, the problems of errors in manual inspection and more time consumption in fault communication are avoided, and the detection efficiency is improved.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A detection method of a robot capsule is characterized by comprising the following steps:
acquiring standard data of the capsule;
detecting actual data of the capsule;
comparing the standard data with the actual data to obtain a difference result of the actual data and the standard data;
and analyzing a difference reason according to the difference result, and outputting a correction suggestion based on the difference reason.
2. The method of claim 1, wherein the standard data comprises one or more of door speed, door acceleration, motor speed, motor acceleration, motor torque, motor current, door gap, door panel gap, door spindle radius of rotation, door screw bearing position, sticker position, rail spacing, rail height difference.
3. The method for the inspection of a robot pod according to claim 2, wherein the step of inspecting the actual data of the pod comprises:
detecting the instantaneous speed of the hatch of the capsule during opening or closing;
calculating an acceleration of the door during opening or closing based on the instantaneous velocity.
4. The method of detecting a robotic pod according to claim 3, wherein the step of calculating the acceleration of the pod door during opening or closing based on the instantaneous velocity is followed by further comprising:
calculating the moment of the cabin door in the opening or closing process according to the acceleration;
and calculating the current of the motor by combining the moment and the inherent parameters of the motor driving the hatch door to open or close.
5. The method for the inspection of a robot pod according to claim 2, wherein the step of inspecting the actual data of the pod comprises:
shooting a door opening picture or a door closing picture through a camera after the cabin door is opened or closed;
and acquiring the door opening clearance or the door closing clearance of the capsule based on the door opening picture or the door closing picture.
6. The method for the inspection of a robot pod according to claim 2, wherein the step of inspecting the actual data of the pod comprises:
shooting an appearance picture of the capsule through a camera;
and acquiring the door plate clearance, the door shaft rotating radius and the door opening and closing screw bearing position of the capsule based on the appearance picture.
7. The method of inspecting a robot pod of claim 6, wherein the step of taking a picture of the pod's appearance via a camera is followed by:
and acquiring the sticker position of the capsule based on the appearance picture.
8. The method for detecting a robotic pod of claim 6 wherein, following the step of taking a picture of the exterior of the pod with a camera, further comprising:
acquiring the sliding rail distance and the sliding rail height difference of the capsule based on the appearance picture;
and calculating the parallelism of the sliding rails by combining the distance between the sliding rails and the height difference of the sliding rails.
9. A detection device of a robot capsule is characterized by comprising:
the acquisition module is used for acquiring standard data of the capsule;
the detection module is used for detecting actual data of the capsule;
the comparison module is used for comparing the standard data with the actual data and obtaining the difference result of the actual data and the standard data; and
and the analysis module is used for analyzing a difference reason according to the difference result and outputting a correction suggestion based on the difference reason.
10. A robot, comprising: a memory and one or more processors, the memory for storing one or more computer programs; characterized in that said one or more computer programs, when executed by said one or more processors, implement the detection method of a robot pod according to any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210890010.1A CN115256464A (en) | 2022-07-27 | 2022-07-27 | Detection method and device for robot capsule, robot and related product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210890010.1A CN115256464A (en) | 2022-07-27 | 2022-07-27 | Detection method and device for robot capsule, robot and related product |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115256464A true CN115256464A (en) | 2022-11-01 |
Family
ID=83770195
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210890010.1A Pending CN115256464A (en) | 2022-07-27 | 2022-07-27 | Detection method and device for robot capsule, robot and related product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115256464A (en) |
-
2022
- 2022-07-27 CN CN202210890010.1A patent/CN115256464A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107272586B (en) | Machine learning device, machine learning method, failure prediction device, and failure prediction system | |
| EP1955830B1 (en) | A method and a control system for monitoring the condition of an industrial robot | |
| US20150301521A1 (en) | Systems, methods, devices and computer readable medium for real and near-real time sensor data capture and analysis | |
| JP6943332B2 (en) | Anomaly detection device and abnormality detection method | |
| US20180348741A1 (en) | Manufacturing line monitoring device, manufacturing line monitoring program, and manufacturing line monitoring method | |
| US11579059B2 (en) | Inspection apparatus and inspection method for inspection target | |
| KR20190005758A (en) | Elevator sensor system calibration | |
| US10941018B2 (en) | Elevator auto-positioning for validating maintenance | |
| US11538148B2 (en) | Defect detection of a component in an assembly | |
| CN111079865A (en) | Detection method and apparatus, electronic device, and medium | |
| KR20140072331A (en) | Method for preliminary surveillance of failure diagnosis | |
| US20130338938A1 (en) | Identifying wind or water turbines for maintenance | |
| CN115256464A (en) | Detection method and device for robot capsule, robot and related product | |
| CN116502172B (en) | Intelligent fault diagnosis method and system for bag type packaging machine | |
| KR20180033844A (en) | Fault Diagnosis System of Industrial Robot | |
| JP2020042668A (en) | Inspection apparatus and machine learning method | |
| KR102198190B1 (en) | Data standardization method considering operating contion for diagnosis of rotating machinery failure and diagnosis method rotating machinery failure using the same | |
| US20060203254A1 (en) | Measurements of an axisymmetric part including helical coil springs | |
| JP2750632B2 (en) | Automatic durability test method for vehicle opening / closing part | |
| EP3499327A1 (en) | Load state diagnosis device and load state diagnosis method for servomotor | |
| CN113591984A (en) | Method and device for detecting equipment operation event, electronic equipment and storage medium | |
| CN108181315B (en) | Image processing-based biscuit damage detection device and detection method | |
| CN105372062B (en) | Air conditioning for automobiles gear train conformability method, system and application are surveyed based on transient current | |
| CN111829783A (en) | Real-time defect detection system for variable-speed rotating mechanism | |
| TWI515521B (en) | Real time monitoring method for feeding device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |